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模型市场

329 个模型,一个端点。

精选模型记录已接入公开市场,并带有价格、上下文、能力、路由状态和来源标签。先筛选工作负载,再把候选模型接入同一个 OpenAI 兼容端点。

路由候选329/329
Claude Fable Latest$1.88/1M
Anthropic Claude Haiku Latest$0.188/1M
Claude Opus Latest$0.94/1M
Anthropic Claude Sonnet Latest$0.564/1M
11提供方1来源标签2M最长上下文$0最低输入价
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329 / 329 个模型

每张卡片都标好来源,也能直接复制成 OpenAI 兼容调用。

这里能一次看清什么?

NextModel 模型市场会同时展示提供方、输入价格、输出价格、上下文长度、延迟估算、能力、使用场景、可用性、路由状态和来源标签,帮助团队在正式导流前收敛模型候选。

OpenRouter目录

This model always redirects to the latest model in the Claude Fable family.

$1.88 / 1M tokens输入$9.40 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

This model always redirects to the latest model in the Anthropic Claude Haiku family.

$0.188 / 1M tokens输入$0.94 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

This model always redirects to the latest model in the Claude Opus family.

$0.94 / 1M tokens输入$4.70 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

This model always redirects to the latest model in the Anthropic Claude Sonnet family.

$0.564 / 1M tokens输入$2.82 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

This model always redirects to the latest model in the Google Gemini Flash family.

$0.282 / 1M tokens输入$1.69 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

This model always redirects to the latest model in the Google Gemini Pro family.

$0.376 / 1M tokens输入$2.26 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

This model always redirects to the latest model in the MoonshotAI Kimi family.

$0.124 / 1M tokens输入$0.658 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

This model always redirects to the latest model in the OpenAI GPT family.

$0.94 / 1M tokens输入$5.64 / 1M tokens输出1.1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

This model always redirects to the latest model in the OpenAI GPT Mini family.

$0.142 / 1M tokens输入$0.846 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Jamba Large 1.7 is the latest model in the Jamba open family, offering improvements in grounding, instruction-following, and overall efficiency. Built on a hybrid SSM-Transformer architecture with a 256K context...

$0.376 / 1M tokens输入$1.50 / 1M tokens输出256k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.752 / 1M tokens输入$1.50 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.132 / 1M tokens输入$0.263 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Aion-2.0 is a variant of DeepSeek V3.2 optimized for immersive roleplaying and storytelling. It is particularly strong at introducing tension, crises, and conflict into stories, making narratives feel more engaging....

$0.152 / 1M tokens输入$0.302 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Aion-RP-Llama-3.1-8B ranks the highest in the character evaluation portion of the RPBench-Auto benchmark, a roleplaying-specific variant of Arena-Hard-Auto, where LLMs evaluate each other’s responses. It is a fine-tuned base model...

$0.152 / 1M tokens输入$0.302 / 1M tokens输出32.8k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Olmo 3 32B Think is a large-scale, 32-billion-parameter model purpose-built for deep reasoning, complex logic chains and advanced instruction-following scenarios. Its capacity enables strong performance on demanding evaluation tasks and...

$0.029 / 1M tokens输入$0.094 / 1M tokens输出65.5k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Nova 2 Lite is a fast, cost-effective reasoning model for everyday workloads that can process text, images, and videos to generate text. Nova 2 Lite demonstrates standout capabilities in processing...

$0.058 / 1M tokens输入$0.47 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Amazon Nova Lite 1.0 is a very low-cost multimodal model from Amazon that focused on fast processing of image, video, and text inputs to generate text output. Amazon Nova Lite...

$0.012 / 1M tokens输入$0.046 / 1M tokens输出300k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Amazon Nova Micro 1.0 is a text-only model that delivers the lowest latency responses in the Amazon Nova family of models at a very low cost. With a context length...

$0.0072 / 1M tokens输入$0.027 / 1M tokens输出128k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Amazon Nova Premier is the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models.

$0.47 / 1M tokens输入$2.35 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Amazon Nova Pro 1.0 is a capable multimodal model from Amazon focused on providing a combination of accuracy, speed, and cost for a wide range of tasks. As of December...

$0.152 / 1M tokens输入$0.602 / 1M tokens输出300k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet(https://openrouter.ai/anthropic/claude-3.5-sonnet) and Opus(https://openrouter.ai/anthropic/claude-3-opus). The model is fine-tuned on top of [Qwen2.5 72B](https://openrouter.ai/qwen/qwen-2.5-72b-instruct).

$0.564 / 1M tokens输入$0.94 / 1M tokens输出16.4k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Claude 3 Haiku is Anthropic's fastest and most compact model for near-instant responsiveness. Quick and accurate targeted performance. See the launch announcement and benchmark results [here](https://www.anthropic.com/news/claude-3-haiku) #multimodal

$0.048 / 1M tokens输入$0.236 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Available through the NextModel gateway via Anthropic.

$0.152 / 1M tokens输入$0.752 / 1M tokens输出上下文
适用场景General chat via Anthropic, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and...

$1.45 / 1M tokens输入$7.23 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...

$0.145 / 1M tokens输入$0.723 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Claude Opus 4 is benchmarked as the world’s best coding model, at time of release, bringing sustained performance on complex, long-running tasks and agent workflows. It sets new benchmarks in...

$2.82 / 1M tokens输入$14.11 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains...

$2.82 / 1M tokens输入$14.11 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and...

$0.723 / 1M tokens输入$3.62 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective...

$0.723 / 1M tokens输入$3.62 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Available through the NextModel gateway via Anthropic.

$5.64 / 1M tokens输入$28.21 / 1M tokens输出上下文
适用场景General chat via Anthropic, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

$0.723 / 1M tokens输入$3.62 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Fast-mode variant of [Opus 4.7](/anthropic/claude-opus-4.7) - identical capabilities with higher output speed at premium 6x pricing. Learn more in Anthropic's docs: https://platform.claude.com/docs/en/build-with-claude/fast-mode

$5.64 / 1M tokens输入$28.21 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token...

$0.723 / 1M tokens输入$3.62 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Fast-mode variant of [Opus 4.8](/anthropic/claude-opus-4.8) - identical capabilities with higher output speed at 2x pricing relative to regular Opus 4.8. Learn more in Anthropic's docs: https://platform.claude.com/docs/en/build-with-claude/fast-mode

$1.88 / 1M tokens输入$9.40 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Claude Sonnet 4 significantly enhances the capabilities of its predecessor, Sonnet 3.7, excelling in both coding and reasoning tasks with improved precision and controllability. Achieving state-of-the-art performance on SWE-bench (72.7%),...

$0.564 / 1M tokens输入$2.82 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with...

$0.434 / 1M tokens输入$2.17 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Anthropic目录

Sonnet 4.6 is Anthropic's most capable Sonnet-class model yet, with frontier performance across coding, agents, and professional work. It excels at iterative development, complex codebase navigation, end-to-end project management with...

$0.434 / 1M tokens输入$2.17 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.094 / 1M tokens输入$0.152 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Trinity Large Thinking is a powerful open source reasoning model from the team at Arcee AI. It shows strong performance in PinchBench, agentic workloads, and reasoning tasks. Launch video: https://youtu.be/Gc82AXLa0Rg?si=4RLn6WBz33qT--B7...

$0.048 / 1M tokens输入$0.152 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.0087 / 1M tokens输入$0.029 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Virtuoso‑Large is Arcee's top‑tier general‑purpose LLM at 72 B parameters, tuned to tackle cross‑domain reasoning, creative writing and enterprise QA. Unlike many 70 B peers, it retains the 128 k...

$0.142 / 1M tokens输入$0.226 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

ERNIE-4.5-VL-424B-A47B is a multimodal Mixture-of-Experts (MoE) model from Baidu’s ERNIE 4.5 series, featuring 424B total parameters with 47B active per token. It is trained jointly on text and image data...

$0.08 / 1M tokens输入$0.236 / 1M tokens输出123k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Seed 1.6 is a general-purpose model released by the ByteDance Seed team. It incorporates multimodal capabilities and adaptive deep thinking with a 256K context window.

$0.048 / 1M tokens输入$0.376 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Seed 1.6 Flash is an ultra-fast multimodal deep thinking model by ByteDance Seed, supporting both text and visual understanding. It features a 256k context window and can generate outputs of...

$0.014 / 1M tokens输入$0.058 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Seed-2.0-Lite is a versatile, cost‑efficient enterprise workhorse that delivers strong multimodal and agent capabilities while offering noticeably lower latency, making it a practical default choice for most production workloads across...

$0.048 / 1M tokens输入$0.376 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Seed-2.0-mini targets latency-sensitive, high-concurrency, and cost-sensitive scenarios, emphasizing fast response and flexible inference deployment. It delivers performance comparable to ByteDance-Seed-1.6, supports 256k context, four reasoning effort modes (minimal/low/medium/high), multimodal understanding,...

$0.02 / 1M tokens输入$0.075 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
ByteDance Seed目录

UI-TARS-1.5 is a multimodal vision-language agent optimized for GUI-based environments, including desktop interfaces, web browsers, mobile systems, and games. Built by ByteDance, it builds upon the UI-TARS framework with reinforcement...

$0.02 / 1M tokens输入$0.038 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to other leading proprietary...

$0.47 / 1M tokens输入$1.88 / 1M tokens输出256k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broadly, it is better at math, code and reasoning and...

$0.029 / 1M tokens输入$0.114 / 1M tokens输出128k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

command-r-plus-08-2024 is an update of the [Command R+](/models/cohere/command-r-plus) with roughly 50% higher throughput and 25% lower latencies as compared to the previous Command R+ version, while keeping the hardware footprint...

$0.47 / 1M tokens输入$1.88 / 1M tokens输出128k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning...

$0.0072 / 1M tokens输入$0.029 / 1M tokens输出128k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Cogito v2.1 671B MoE represents one of the strongest open models globally, matching performance of frontier closed and open models. This model is trained using self play with reinforcement learning...

$0.236 / 1M tokens输入$0.236 / 1M tokens输出128k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
DeepSeek目录

DeepSeek V4 Flash 是长上下文、低成本候选,适合需要中文能力和批量友好定价的团队。

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景中文问答, general chat
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
DeepSeek目录

Available through the NextModel gateway via DeepSeek.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景中文问答, general chat
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

DeepSeek-V3 is the latest model from the DeepSeek team, building upon the instruction following and coding abilities of the previous versions. Pre-trained on nearly 15 trillion tokens, the reported evaluations...

$0.038 / 1M tokens输入$0.152 / 1M tokens输出163.8k上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the [DeepSeek V3](/deepseek/deepseek-chat-v3) model and performs really well...

$0.038 / 1M tokens输入$0.146 / 1M tokens输出163.8k上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

$0.041 / 1M tokens输入$0.149 / 1M tokens输出163.8k上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....

$0.132 / 1M tokens输入$0.47 / 1M tokens输出163.8k上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active...

$0.094 / 1M tokens输入$0.405 / 1M tokens输出163.8k上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across...

$0.152 / 1M tokens输入$0.152 / 1M tokens输出8.2k上下文
适用场景中文问答, general chat
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's...

$0.052 / 1M tokens输入$0.179 / 1M tokens输出163.8k上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

$0.043 / 1M tokens输入$0.065 / 1M tokens输出163.8k上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
DeepSeek目录

DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

$0.052 / 1M tokens输入$0.078 / 1M tokens输出163.8k上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and...

$0.017 / 1M tokens输入$0.035 / 1M tokens输出1M上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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DeepSeek目录

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...

$0.082 / 1M tokens输入$0.165 / 1M tokens输出1M上下文
适用场景中文问答, general chat
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

Starting at $0 / 1M tokens输入Starting at $0 / 1M tokens输出上下文
适用场景中文问答, general chat
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

Starting at $0 / 1M tokens输入Starting at $0 / 1M tokens输出上下文
适用场景中文问答, general chat
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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Volcengine目录

Doubao Seed 2.0 Mini 是目前通过 NextModel 公共网关暴露的最低成本生产模型。它适合作为中文问答、分类、摘要和轻量多模态任务的默认选择。

Starting at $0.0043 / 1M tokens输入Starting at $0.041 / 1M tokens输出上下文
适用场景中文问答, general chat
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

Starting at $0 / 1M tokens输入Starting at $0 / 1M tokens输出上下文
适用场景中文问答, general chat
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Volcengine目录

Available through the NextModel gateway via Volcengine.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.029 / 1M tokens输入$0.029 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
Zhipu AI (GLM)目录

Available through the NextModel gateway via Zhipu AI (GLM).

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景中文问答, general chat
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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Google目录

Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater...

$0.043 / 1M tokens输入$0.362 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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Google目录

Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image generation,...

$0.058 / 1M tokens输入$0.47 / 1M tokens输出32.8k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉
平台整理NextModel gateway catalog (Go origin)
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Google目录

Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...

$0.02 / 1M tokens输入$0.075 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Available through the NextModel gateway via Google.

$0.02 / 1M tokens输入$0.075 / 1M tokens输出上下文
适用场景General chat via Google, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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Google目录

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...

$0.236 / 1M tokens输入$1.88 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...

$0.236 / 1M tokens输入$1.88 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...

$0.236 / 1M tokens输入$1.88 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance. It delivers near Pro level reasoning and tool...

$0.072 / 1M tokens输入$0.434 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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Google目录

Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and...

$0.376 / 1M tokens输入$2.26 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and...

$0.376 / 1M tokens输入$2.26 / 1M tokens输出65.5k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemini 3.1 Flash Image, a.k.a. "Nano Banana 2," is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced...

$0.094 / 1M tokens输入$0.564 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemini 3.1 Flash Image Preview, a.k.a. "Nano Banana 2," is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines...

$0.094 / 1M tokens输入$0.564 / 1M tokens输出65.5k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemini 3.1 Flash Lite is Google’s GA high-efficiency multimodal model optimized for low-latency, high-volume workloads. It supports text, image, video, audio, and PDF inputs, and is designed for lightweight agentic...

$0.036 / 1M tokens输入$0.217 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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Google目录

Gemini 3.1 Flash Lite Preview is Google's high-efficiency model optimized for high-volume use cases. It outperforms Gemini 2.5 Flash Lite on overall quality and approaches Gemini 2.5 Flash performance across...

$0.048 / 1M tokens输入$0.282 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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Google目录

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...

$0.376 / 1M tokens输入$2.26 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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Google目录

Gemini 3.1 Pro Preview Custom Tools is a variant of Gemini 3.1 Pro that improves tool selection behavior by preventing overuse of a general bash tool when more efficient third-party...

$0.376 / 1M tokens输入$2.26 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...

$0.217 / 1M tokens输入$1.30 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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Google目录

Gemma 2 27B by Google is an open model built from the same research and technology used to create the [Gemini models](/models?q=gemini). Gemma models are well-suited for a variety of...

$0.123 / 1M tokens输入$0.123 / 1M tokens输出8.2k上下文
适用场景General chat via Google, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

$0.01 / 1M tokens输入$0.029 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

$0.016 / 1M tokens输入$0.03 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

$0.01 / 1M tokens输入$0.02 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemma 3n E4B-it is optimized for efficient execution on mobile and low-resource devices, such as phones, laptops, and tablets. It supports multimodal inputs—including text, visual data, and audio—enabling diverse tasks...

$0.012 / 1M tokens输入$0.023 / 1M tokens输出32.8k上下文
适用场景General chat via Google, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
查看详情
Google目录

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

$0.012 / 1M tokens输入$0.062 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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Google目录

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

$0.023 / 1M tokens输入$0.067 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

One of the highest performing and most popular fine-tunes of Llama 2 13B, with rich descriptions and roleplay. #merge

$0.012 / 1M tokens输入$0.012 / 1M tokens输出8.2k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Granite-4.0-H-Micro is a 3B parameter from the Granite 4 family of models. These models are the latest in a series of models released by IBM. They are fine-tuned for long...

$0.0043 / 1M tokens输入$0.022 / 1M tokens输出131k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Granite 4.1 8B is a dense, decoder-only 8-billion-parameter language model from IBM, part of the Granite 4.1 family. It supports a 131K-token context window and is designed for enterprise tasks...

$0.01 / 1M tokens输入$0.02 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Mercury 2 is an extremely fast reasoning LLM, and the first reasoning diffusion LLM (dLLM). Instead of generating tokens sequentially, Mercury 2 produces and refines multiple tokens in parallel, achieving...

$0.048 / 1M tokens输入$0.142 / 1M tokens输出128k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Ling-2.6-1T is an instant (instruct) model from inclusionAI and the company’s trillion-parameter flagship, designed for real-world agents that require fast execution and high efficiency at scale. It uses a “fast...

$0.014 / 1M tokens输入$0.119 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency....

$0.0029 / 1M tokens输入$0.0058 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
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OpenRouter目录

Ring-2.6-1T is a 1T-parameter-scale thinking model with 63B active parameters, built for real-world agent workflows that require both strong capability and operational efficiency. It is optimized for coding agents, tool...

$0.014 / 1M tokens输入$0.119 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.47 / 1M tokens输入$1.88 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.47 / 1M tokens输入$1.88 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
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Moonshot AI目录

Kimi K2.6 是面向长上下文中文场景的模型候选,适合文档密集型团队在成本、上下文长度和国内模型覆盖之间做权衡。

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景中文问答, general chat
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Moonshot AI目录

Available through the NextModel gateway via Moonshot AI.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景中文问答, general chat
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OpenRouter目录

KAT-Coder-Pro V2 is the latest high-performance model in KwaiKAT’s KAT-Coder series, designed for complex enterprise-grade software engineering and SaaS integration. It builds on the agentic coding strengths of earlier versions,...

$0.058 / 1M tokens输入$0.226 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.0058 / 1M tokens输入$0.023 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

An attempt to recreate Claude-style verbosity, but don't expect the same level of coherence or memory. Meant for use in roleplay/narrative situations.

$0.142 / 1M tokens输入$0.188 / 1M tokens输出8k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.027 / 1M tokens输入$0.027 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...

$0.075 / 1M tokens输入$0.075 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...

$0.0043 / 1M tokens输入$0.0058 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.065 / 1M tokens输入$0.065 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate...

$0.0058 / 1M tokens输入$0.039 / 1M tokens输出60k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...

$0.01 / 1M tokens输入$0.064 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...

$0.02 / 1M tokens输入$0.061 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...

$0.029 / 1M tokens输入$0.114 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

$0.02 / 1M tokens输入$0.058 / 1M tokens输出1.3M上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM...

$0.035 / 1M tokens输入$0.035 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...

$0.013 / 1M tokens输入$0.027 / 1M tokens输出16.4k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.016 / 1M tokens输入$0.067 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

WizardLM-2 8x22B is Microsoft AI's most advanced Wizard model. It demonstrates highly competitive performance compared to leading proprietary models, and it consistently outperforms all existing state-of-the-art opensource models. It is...

$0.117 / 1M tokens输入$0.117 / 1M tokens输出65.5k上下文
适用场景General chat via OpenRouter, API workloads
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MiniMax目录

Available through the NextModel gateway via MiniMax.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景中文问答, general chat
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MiniMax目录

Available through the NextModel gateway via MiniMax.

$0 / 1M tokens输入$0 / 1M tokens输出上下文
适用场景中文问答, general chat
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MiniMax目录

MiniMax-01 is a combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding. It has 456 billion parameters, with 45.9 billion parameters activated per inference, and can handle a context...

$0.038 / 1M tokens输入$0.208 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
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MiniMax目录

MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...

$0.075 / 1M tokens输入$0.414 / 1M tokens输出1M上下文
适用场景中文问答, general chat
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MiniMax目录

MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...

$0.049 / 1M tokens输入$0.188 / 1M tokens输出204.8k上下文
适用场景中文问答, general chat
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MiniMax目录

MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in tone and personality, it supports rich message...

$0.058 / 1M tokens输入$0.226 / 1M tokens输出65.5k上下文
适用场景中文问答, general chat
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MiniMax目录

MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world...

$0.055 / 1M tokens输入$0.179 / 1M tokens输出204.8k上下文
适用场景中文问答, general chat
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MiniMax目录

MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1...

$0.029 / 1M tokens输入$0.169 / 1M tokens输出204.8k上下文
适用场景中文问答, general chat
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MiniMax目录

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...

$0.048 / 1M tokens输入$0.188 / 1M tokens输出204.8k上下文
适用场景中文问答, general chat
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MiniMax目录

MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding,...

$0.058 / 1M tokens输入$0.226 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. [Blog Post](https://mistral.ai/news/codestral-25-08)

$0.058 / 1M tokens输入$0.169 / 1M tokens输出256k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.075 / 1M tokens输入$0.376 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language...

$0.038 / 1M tokens输入$0.038 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
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OpenRouter目录

The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.

$0.02 / 1M tokens输入$0.02 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.

$0.029 / 1M tokens输入$0.029 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

This is Mistral AI's flagship model, Mistral Large 2 (version `mistral-large-2407`). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/)....

$0.376 / 1M tokens输入$1.13 / 1M tokens输出128k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/)....

$0.376 / 1M tokens输入$1.13 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.

$0.094 / 1M tokens输入$0.282 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Mistral Medium 3 is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost...

$0.075 / 1M tokens输入$0.376 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...

$0.282 / 1M tokens输入$1.41 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...

$0.075 / 1M tokens输入$0.376 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

$0.0043 / 1M tokens输入$0.0058 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Mistral Saba is a 24B-parameter language model specifically designed for the Middle East and South Asia, delivering accurate and contextually relevant responses while maintaining efficient performance. Trained on curated regional...

$0.038 / 1M tokens输入$0.114 / 1M tokens输出32.8k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed...

$0.01 / 1M tokens输入$0.016 / 1M tokens输出32.8k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...

$0.029 / 1M tokens输入$0.114 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Mistral Small 3.1 24B Instruct is an upgraded variant of Mistral Small 3 (2501), featuring 24 billion parameters with advanced multimodal capabilities. It provides state-of-the-art performance in text-based reasoning and...

$0.067 / 1M tokens输入$0.106 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compared to the 3.1 release, version 3.2 significantly improves accuracy on...

$0.014 / 1M tokens输入$0.038 / 1M tokens输出256k上下文
适用场景图像理解, multimodal chat
路由已配置
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OpenRouter目录

Mistral's official instruct fine-tuned version of [Mixtral 8x22B](/models/mistralai/mixtral-8x22b). It uses 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. Its strengths include: - strong math, coding,...

$0.376 / 1M tokens输入$1.13 / 1M tokens输出65.5k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Voxtral Small is an enhancement of Mistral Small 3, incorporating state-of-the-art audio input capabilities while retaining best-in-class text performance. It excels at speech transcription, translation and audio understanding. Input audio...

$0.02 / 1M tokens输入$0.058 / 1M tokens输出32k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...

$0.109 / 1M tokens输入$0.434 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2). It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32...

$0.114 / 1M tokens输入$0.47 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-of-Experts (MoE) architecture introduced in...

$0.114 / 1M tokens输入$0.47 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed...

$0.071 / 1M tokens输入$0.382 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and...

$0.124 / 1M tokens输入$0.658 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
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OpenRouter目录

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...

$0.116 / 1M tokens输入$0.579 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Morph's fastest apply model for code edits. ~10,500 tokens/sec with 96% accuracy for rapid code transformations. The model requires the prompt to be in the following format: <instruction>{instruction}</instruction> <code>{initial_code}</code> <update>{edit_snippet}</update>...

$0.152 / 1M tokens输入$0.226 / 1M tokens输出81.9k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Morph's high-accuracy apply model for complex code edits. ~4,500 tokens/sec with 98% accuracy for precise code transformations. The model requires the prompt to be in the following format: <instruction>{instruction}</instruction> <code>{initial_code}</code>...

$0.169 / 1M tokens输入$0.357 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Hermes 3 is a generalist language model with many improvements over Hermes 2, including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the...

$0.188 / 1M tokens输入$0.188 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Hermes 3 is a generalist language model with many improvements over [Hermes 2](/models/nousresearch/nous-hermes-2-mistral-7b-dpo), including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the...

$0.132 / 1M tokens输入$0.132 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Hermes 4 is a large-scale reasoning model built on Meta-Llama-3.1-405B and released by Nous Research. It introduces a hybrid reasoning mode, where the model can choose to deliberate internally with...

$0.188 / 1M tokens输入$0.564 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Hermes 4 70B is a hybrid reasoning model from Nous Research, built on Meta-Llama-3.1-70B. It introduces the same hybrid mode as the larger 405B release, allowing the model to either...

$0.025 / 1M tokens输入$0.075 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.075 / 1M tokens输入$0.075 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

NVIDIA Nemotron 3 Nano 30B A3B is a small language MoE model with highest compute efficiency and accuracy for developers to build specialized agentic AI systems. The model is fully...

$0.01 / 1M tokens输入$0.038 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid MoE model, activating just 12B parameters for maximum compute efficiency and accuracy in complex multi-agent applications. Built on a hybrid Mamba-Transformer...

$0.017 / 1M tokens输入$0.085 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...

$0.094 / 1M tokens输入$0.414 / 1M tokens输出512.3k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data up to Sep 2021.

$0.094 / 1M tokens输入$0.282 / 1M tokens输出16.4k上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出工具调用JSON 模式
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data up to Sep 2021.

$0.188 / 1M tokens输入$0.376 / 1M tokens输出4.1k上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出工具调用JSON 模式
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

This model offers four times the context length of gpt-3.5-turbo, allowing it to support approximately 20 pages of text in a single request at a higher cost. Training data: up...

$0.564 / 1M tokens输入$0.752 / 1M tokens输出16.4k上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出工具调用JSON 模式
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

This model is a variant of GPT-3.5 Turbo tuned for instructional prompts and omitting chat-related optimizations. Training data: up to Sep 2021.

$0.282 / 1M tokens输入$0.376 / 1M tokens输出4.1k上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

OpenAI's flagship model, GPT-4 is a large-scale multimodal language model capable of solving difficult problems with greater accuracy than previous models due to its broader general knowledge and advanced reasoning...

$5.64 / 1M tokens输入$11.28 / 1M tokens输出8.2k上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出工具调用JSON 模式
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

The latest GPT-4 Turbo model with vision capabilities. Vision requests can now use JSON mode and function calling. Training data: up to December 2023.

$1.88 / 1M tokens输入$5.64 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

The preview GPT-4 model with improved instruction following, JSON mode, reproducible outputs, parallel function calling, and more. Training data: up to Dec 2023. **Note:** heavily rate limited by OpenAI while...

$1.88 / 1M tokens输入$5.64 / 1M tokens输出128k上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and...

$0.289 / 1M tokens输入$1.16 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard...

$0.058 / 1M tokens输入$0.231 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million...

$0.014 / 1M tokens输入$0.058 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as...

$0.362 / 1M tokens输入$1.45 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as...

$0.94 / 1M tokens输入$2.82 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

The 2024-08-06 version of GPT-4o offers improved performance in structured outputs, with the ability to supply a JSON schema in the respone_format. Read more [here](https://openai.com/index/introducing-structured-outputs-in-the-api/). GPT-4o ("o" for "omni") is...

$0.47 / 1M tokens输入$1.88 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

The 2024-11-20 version of GPT-4o offers a leveled-up creative writing ability with more natural, engaging, and tailored writing to improve relevance & readability. It’s also better at working with uploaded...

$0.47 / 1M tokens输入$1.88 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...

$0.022 / 1M tokens输入$0.087 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...

$0.029 / 1M tokens输入$0.114 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

Available through the NextModel gateway via OpenAI.

$0.029 / 1M tokens输入$0.114 / 1M tokens输出上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

Available through the NextModel gateway via OpenAI.

$0.47 / 1M tokens输入$1.88 / 1M tokens输出上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5 is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy...

$0.181 / 1M tokens输入$1.45 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

Available through the NextModel gateway via OpenAI.

$0.236 / 1M tokens输入$1.88 / 1M tokens输出上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

Available through the NextModel gateway via OpenAI.

$0.236 / 1M tokens输入$1.88 / 1M tokens输出上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

[GPT-5](https://openrouter.ai/openai/gpt-5) Image combines OpenAI's GPT-5 model with state-of-the-art image generation capabilities. It offers major improvements in reasoning, code quality, and user experience while incorporating GPT Image 1's superior instruction following,...

$1.88 / 1M tokens输入$1.88 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5 Image Mini combines OpenAI's advanced language capabilities, powered by [GPT-5 Mini](https://openrouter.ai/openai/gpt-5-mini), with GPT Image 1 Mini for efficient image generation. This natively multimodal model features superior instruction following, text...

$0.47 / 1M tokens输入$0.376 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost....

$0.036 / 1M tokens输入$0.289 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...

$0.0072 / 1M tokens输入$0.058 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5 Pro is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and...

$2.82 / 1M tokens输入$22.57 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5.1 is the latest frontier-grade model in the GPT-5 series, offering stronger general-purpose reasoning, improved instruction adherence, and a more natural conversational style compared to GPT-5. It uses adaptive reasoning...

$0.181 / 1M tokens输入$1.45 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

Available through the NextModel gateway via OpenAI.

$0.236 / 1M tokens输入$1.88 / 1M tokens输出上下文
适用场景General chat via OpenAI, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5.1-Codex is a specialized version of GPT-5.1 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....

$0.236 / 1M tokens输入$1.88 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5.1-Codex-Max is OpenAI’s latest agentic coding model, designed for long-running, high-context software development tasks. It is based on an updated version of the 5.1 reasoning stack and trained on agentic...

$0.236 / 1M tokens输入$1.88 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5.1-Codex-Mini is a smaller and faster version of GPT-5.1-Codex

$0.048 / 1M tokens输入$0.376 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5.2 is the latest frontier-grade model in the GPT-5 series, offering stronger agentic and long context perfomance compared to GPT-5.1. It uses adaptive reasoning to allocate computation dynamically, responding quickly...

$0.253 / 1M tokens输入$2.03 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5.2 Chat (AKA Instant) is the fast, lightweight member of the 5.2 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on...

$0.33 / 1M tokens输入$2.63 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5.2-Codex is an upgraded version of GPT-5.1-Codex optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....

$0.33 / 1M tokens输入$2.63 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5.2 Pro is OpenAI’s most advanced model, offering major improvements in agentic coding and long context performance over GPT-5 Pro. It is optimized for complex tasks that require step-by-step reasoning,...

$3.95 / 1M tokens输入$31.60 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5.3 Chat is an update to ChatGPT's most-used model that makes everyday conversations smoother, more useful, and more directly helpful. It delivers more accurate answers with better contextualization and significantly...

$0.33 / 1M tokens输入$2.63 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5.3-Codex is OpenAI’s most advanced agentic coding model, combining the frontier software engineering performance of GPT-5.2-Codex with the broader reasoning and professional knowledge capabilities of GPT-5.2. It achieves state-of-the-art results...

$0.33 / 1M tokens输入$2.63 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5.4 is OpenAI’s latest frontier model, unifying the Codex and GPT lines into a single system. It features a 1M+ token context window (922K input, 128K output) with support for...

$0.47 / 1M tokens输入$2.82 / 1M tokens输出1.1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

[GPT-5.4](https://openrouter.ai/openai/gpt-5.4) Image 2 combines OpenAI's GPT-5.4 model with state-of-the-art image generation capabilities from GPT Image 2. It enables rich multimodal workflows, allowing users to seamlessly move between reasoning, coding, and...

$1.50 / 1M tokens输入$2.82 / 1M tokens输出272k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5.4 mini brings the core capabilities of GPT-5.4 to a faster, more efficient model optimized for high-throughput workloads. It supports text and image inputs with strong performance across reasoning, coding,...

$0.109 / 1M tokens输入$0.651 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is designed for low-latency...

$0.029 / 1M tokens输入$0.181 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenAI目录

GPT-5.4 Pro is OpenAI's most advanced model, building on GPT-5.4's unified architecture with enhanced reasoning capabilities for complex, high-stakes tasks. It features a 1M+ token context window (922K input, 128K...

$5.64 / 1M tokens输入$33.85 / 1M tokens输出1.1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenAI目录

GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token...

$0.94 / 1M tokens输入$5.64 / 1M tokens输出1.1M上下文
适用场景图像理解, multimodal chat
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OpenAI目录

GPT-5.5 Pro is OpenAI’s high-capability model optimized for deep reasoning and accuracy on complex, high-stakes workloads. It features a 1M+ token context window (922K input, 128K output) with support for...

$5.64 / 1M tokens输入$33.85 / 1M tokens输出1.1M上下文
适用场景图像理解, multimodal chat
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OpenAI目录

The gpt-audio model is OpenAI's first generally available audio model. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Audio is priced...

$0.47 / 1M tokens输入$1.88 / 1M tokens输出128k上下文
适用场景General chat via OpenAI, API workloads
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OpenAI目录

A cost-efficient version of GPT Audio. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Input is priced at $0.60 per million...

$0.114 / 1M tokens输入$0.451 / 1M tokens输出128k上下文
适用场景General chat via OpenAI, API workloads
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OpenAI目录

GPT Chat Latest points to OpenAI's stable API alias `chat-latest` that always resolves to the latest Instant chat model used in ChatGPT. As OpenAI rolls out new Instant model updates...

$0.94 / 1M tokens输入$5.64 / 1M tokens输出400k上下文
适用场景图像理解, multimodal chat
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OpenAI目录

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...

$0.0087 / 1M tokens输入$0.035 / 1M tokens输出131.1k上下文
适用场景General chat via OpenAI, API workloads
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OpenAI目录

gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...

$0.0058 / 1M tokens输入$0.027 / 1M tokens输出131.1k上下文
适用场景General chat via OpenAI, API workloads
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OpenAI目录

gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model offers lower latency for safety tasks like content classification, LLM filtering, and trust...

$0.014 / 1M tokens输入$0.058 / 1M tokens输出131.1k上下文
适用场景General chat via OpenAI, API workloads
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OpenAI目录

The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...

$2.82 / 1M tokens输入$11.28 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
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OpenAI目录

The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...

$28.21 / 1M tokens输入$112.85 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
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OpenAI目录

o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following....

$0.289 / 1M tokens输入$1.16 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
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OpenAI目录

Available through the NextModel gateway via OpenAI.

$1.88 / 1M tokens输入$7.52 / 1M tokens输出上下文
适用场景General chat via OpenAI, API workloads
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OpenAI目录

OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to...

$0.208 / 1M tokens输入$0.828 / 1M tokens输出200k上下文
适用场景General chat via OpenAI, API workloads
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OpenAI目录

OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...

$0.208 / 1M tokens输入$0.828 / 1M tokens输出200k上下文
适用场景General chat via OpenAI, API workloads
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OpenAI目录

The o-series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o3-pro model uses more compute to think harder and provide consistently...

$3.76 / 1M tokens输入$15.05 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
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OpenAI目录

OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning...

$0.159 / 1M tokens输入$0.637 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
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OpenAI目录

Available through the NextModel gateway via OpenAI.

$0.376 / 1M tokens输入$1.50 / 1M tokens输出上下文
适用场景General chat via OpenAI, API workloads
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OpenAI目录

OpenAI o4-mini-high is the same model as [o4-mini](/openai/o4-mini) with reasoning_effort set to high. OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining...

$0.208 / 1M tokens输入$0.828 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Perceptron Mk1 (Mark One) is Perceptron's highest-quality vision-language model for video and embodied reasoning.** It accepts image and video inputs paired with natural language queries, and produces detailed visual understanding...

$0.029 / 1M tokens输入$0.282 / 1M tokens输出32.8k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Sonar is lightweight, affordable, fast, and simple to use — now featuring citations and the ability to customize sources. It is designed for companies seeking to integrate lightweight question-and-answer features...

$0.188 / 1M tokens输入$0.188 / 1M tokens输出127.1k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Sonar Deep Research is a research-focused model designed for multi-step retrieval, synthesis, and reasoning across complex topics. It autonomously searches, reads, and evaluates sources, refining its approach as it gathers...

$0.376 / 1M tokens输入$1.50 / 1M tokens输出128k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro) For enterprises seeking more advanced capabilities, the Sonar Pro API can handle in-depth, multi-step queries with added extensibility, like...

$0.564 / 1M tokens输入$2.82 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Exclusively available on the OpenRouter API, Sonar Pro's new Pro Search mode is Perplexity's most advanced agentic search system. It is designed for deeper reasoning and analysis. Pricing is based...

$0.564 / 1M tokens输入$2.82 / 1M tokens输出200k上下文
适用场景图像理解, multimodal chat
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OpenRouter目录

Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro) Sonar Reasoning Pro is a premier reasoning model powered by DeepSeek R1 with Chain of Thought (CoT). Designed for...

$0.376 / 1M tokens输入$1.50 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出视觉长上下文
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.038 / 1M tokens输入$0.075 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.02 / 1M tokens输入$0.038 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.038 / 1M tokens输入$0.208 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...

$0.068 / 1M tokens输入$0.075 / 1M tokens输出32.8k上下文
适用场景General chat via OpenRouter, API workloads
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流式输出工具调用JSON 模式
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OpenRouter目录

Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...

$0.0087 / 1M tokens输入$0.02 / 1M tokens输出32.8k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in **code generation**, **code reasoning**...

$0.124 / 1M tokens输入$0.188 / 1M tokens输出32.8k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.

$0.049 / 1M tokens输入$0.148 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.

$0.049 / 1M tokens输入$0.148 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.

$0.049 / 1M tokens输入$0.148 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.

$0.152 / 1M tokens输入$0.188 / 1M tokens输出128k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉长上下文
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OpenRouter目录

Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...

$0.02 / 1M tokens输入$0.046 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and...

$0.087 / 1M tokens输入$0.343 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...

$0.017 / 1M tokens输入$0.02 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...

$0.02 / 1M tokens输入$0.02 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique...

$0.023 / 1M tokens输入$0.094 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and...

$0.01 / 1M tokens输入$0.038 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking. The model is designed specifically for “thinking mode,” where internal reasoning traces are separated...

$0.016 / 1M tokens输入$0.075 / 1M tokens输出81.9k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式
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OpenRouter目录

Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...

$0.016 / 1M tokens输入$0.054 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between "thinking" mode for math,...

$0.01 / 1M tokens输入$0.075 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team. It is optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning over...

$0.042 / 1M tokens输入$0.34 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and agentic tool use. Built on the...

$0.014 / 1M tokens输入$0.052 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen3 Coder Flash is Alibaba's fast and cost efficient version of their proprietary Qwen3 Coder Plus. It is a powerful coding agent model specializing in autonomous programming via tool calling...

$0.038 / 1M tokens输入$0.184 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...

$0.022 / 1M tokens输入$0.152 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen3 Coder Plus is Alibaba's proprietary version of the Open Source Qwen3 Coder 480B A35B. It is a powerful coding agent model specializing in autonomous programming via tool calling and...

$0.123 / 1M tokens输入$0.612 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen3-Max is an updated release built on the Qwen3 series, offering major improvements in reasoning, instruction following, multilingual support, and long-tail knowledge coverage compared to the January 2025 version. It...

$0.148 / 1M tokens输入$0.734 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen3-Max-Thinking is the flagship reasoning model in the Qwen3 series, designed for high-stakes cognitive tasks that require deep, multi-step reasoning. By significantly scaling model capacity and reinforcement learning compute, it...

$0.148 / 1M tokens输入$0.734 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
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OpenRouter目录

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...

$0.017 / 1M tokens输入$0.208 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
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OpenRouter目录

Qwen3-Next-80B-A3B-Thinking is a reasoning-first chat model in the Qwen3-Next line that outputs structured “thinking” traces by default. It’s designed for hard multi-step problems; math proofs, code synthesis/debugging, logic, and agentic...

$0.019 / 1M tokens输入$0.148 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
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OpenRouter目录

Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...

$0.038 / 1M tokens输入$0.166 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
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OpenRouter目录

Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video. The Thinking model is optimized for multimodal reasoning in STEM and math....

$0.049 / 1M tokens输入$0.49 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following for general multimodal tasks. It excels in perception...

$0.025 / 1M tokens输入$0.098 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3-VL-30B-A3B-Thinking is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Thinking variant enhances reasoning in STEM, math, and complex tasks. It excels...

$0.025 / 1M tokens输入$0.294 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video. With 32 billion parameters, it combines deep visual perception with advanced text...

$0.02 / 1M tokens输入$0.08 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon...

$0.016 / 1M tokens输入$0.094 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3-VL-8B-Thinking is the reasoning-optimized variant of the Qwen3-VL-8B multimodal model, designed for advanced visual and textual reasoning across complex scenes, documents, and temporal sequences. It integrates enhanced multimodal alignment and...

$0.023 / 1M tokens输入$0.258 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of...

$0.049 / 1M tokens输入$0.392 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of...

$0.038 / 1M tokens输入$0.294 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse mixture-of-experts model, achieving higher inference efficiency. Its overall...

$0.027 / 1M tokens输入$0.188 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...

$0.072 / 1M tokens输入$0.462 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...

$0.02 / 1M tokens输入$0.029 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the...

$0.013 / 1M tokens输入$0.049 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In a variety of...

$0.049 / 1M tokens输入$0.294 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3.5 Plus (April 2026) is a large-scale multimodal language model from Alibaba. It accepts text, image, and video input and produces text output, with a 1M token context window. This...

$0.058 / 1M tokens输入$0.34 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs...

$0.055 / 1M tokens输入$0.598 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...

$0.027 / 1M tokens输入$0.188 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3.6 Flash is a fast, efficient language model from Alibaba's Qwen 3.6 series. It supports text, image, and video input with a 1M token context window. Tiered pricing kicks in...

$0.036 / 1M tokens输入$0.213 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3.6-Max-Preview is a proprietary frontier model from Alibaba Cloud built on a sparse mixture-of-experts architecture with approximately 1 trillion total parameters. It is optimized for agentic coding, tool use, and...

$0.197 / 1M tokens输入$1.17 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...

$0.062 / 1M tokens输入$0.367 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with particular strengths in coding, office and productivity tasks,...

$0.236 / 1M tokens输入$0.706 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Qwen3.7-Plus is a cost-effective model in Alibaba's Qwen3.7 series. It supports text and image input with text output, building on the series' text capabilities with a comprehensive upgrade to its...

$0.061 / 1M tokens输入$0.242 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Reka Edge is an extremely efficient 7B multimodal vision-language model that accepts image/video+text inputs and generates text outputs. This model is optimized specifically to deliver industry-leading performance in image understanding,...

$0.02 / 1M tokens输入$0.02 / 1M tokens输出16.4k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用视觉
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Reka Flash 3 is a general-purpose, instruction-tuned large language model with 21 billion parameters, developed by Reka. It excels at general chat, coding tasks, instruction-following, and function calling. Featuring a...

$0.02 / 1M tokens输入$0.038 / 1M tokens输出65.5k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Relace Apply 3 is a specialized code-patching LLM that merges AI-suggested edits straight into your source files. It can apply updates from GPT-4o, Claude, and others into your files at...

$0.161 / 1M tokens输入$0.236 / 1M tokens输出256k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

The relace-search model uses 4-12 `view_file` and `grep` tools in parallel to explore a codebase and return relevant files to the user request. In contrast to RAG, relace-search performs agentic...

$0.188 / 1M tokens输入$0.564 / 1M tokens输出256k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Lunaris 8B is a versatile generalist and roleplaying model based on Llama 3. It's a strategic merge of multiple models, designed to balance creativity with improved logic and general knowledge....

$0.0087 / 1M tokens输入$0.01 / 1M tokens输出8.2k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.564 / 1M tokens输入$0.564 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Euryale L3.1 70B v2.2 is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). It is the successor of [Euryale L3 70B v2.1](/models/sao10k/l3-euryale-70b).

$0.161 / 1M tokens输入$0.161 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Euryale L3.3 70B is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). It is the successor of [Euryale L3 70B v2.2](/models/sao10k/l3-euryale-70b).

$0.123 / 1M tokens输入$0.142 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Step 3.5 Flash is StepFun's most capable open-source foundation model. Built on a sparse Mixture of Experts (MoE) architecture, it selectively activates only 11B of its 196B parameters per token....

$0.017 / 1M tokens输入$0.058 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Step 3.7 Flash is StepFun's latest high-efficiency multimodal Mixture-of-Experts model. It pairs a 196B-parameter language backbone with a vision encoder for native image and video understanding, activating roughly 11B parameters...

$0.038 / 1M tokens输入$0.217 / 1M tokens输出262.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Available through the NextModel gateway via OpenRouter.

$0.161 / 1M tokens输入$0.639 / 1M tokens输出上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive benchmark...

$0.027 / 1M tokens输入$0.109 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Hy3 preview is a high-efficiency Mixture-of-Experts model from Tencent designed for agentic workflows and production use. It supports configurable reasoning levels across disabled, low, and high modes, allowing it to...

$0.013 / 1M tokens输入$0.041 / 1M tokens输出262.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Uncensored and creative writing model based on Mistral Small 3.2 24B with good recall, prompt adherence, and intelligence.

$0.058 / 1M tokens输入$0.094 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Rocinante 12B is designed for engaging storytelling and rich prose. Early testers have reported: - Expanded vocabulary with unique and expressive word choices - Enhanced creativity for vivid narratives -...

$0.033 / 1M tokens输入$0.081 / 1M tokens输出65.5k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Skyfall 36B v2 is an enhanced iteration of Mistral Small 2501, specifically fine-tuned for improved creativity, nuanced writing, role-playing, and coherent storytelling.

$0.104 / 1M tokens输入$0.152 / 1M tokens输出32.8k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

UnslopNemo v4.1 is the latest addition from the creator of Rocinante, designed for adventure writing and role-play scenarios.

$0.075 / 1M tokens输入$0.075 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

A recreation trial of the original MythoMax-L2-B13 but with updated models. #merge

$0.085 / 1M tokens输入$0.123 / 1M tokens输出6.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出JSON 模式
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Solar Pro 3 is Upstage's powerful Mixture-of-Experts (MoE) language model. With 102B total parameters and 12B active parameters per forward pass, it delivers exceptional performance while maintaining computational efficiency. Optimized...

$0.029 / 1M tokens输入$0.114 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Palmyra X5 is Writer's most advanced model, purpose-built for building and scaling AI agents across the enterprise. It delivers industry-leading speed and efficiency on context windows up to 1 million...

$0.114 / 1M tokens输入$1.13 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Grok 4.20 is a reasoning model from SpaceXAI with industry-leading speed and agentic tool calling capabilities. It combines the lowest hallucination rate on the market with strict prompt adherance, delivering...

$0.236 / 1M tokens输入$0.47 / 1M tokens输出2M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

Grok 4.20 Multi-Agent is a variant of SpaceXAI’s Grok 4.20 designed for collaborative, agent-based workflows. Multiple agents operate in parallel to conduct deep research, coordinate tool use, and synthesize information...

$0.236 / 1M tokens输入$0.47 / 1M tokens输出2M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
X Ai目录

Grok 4.3 is a reasoning model from SpaceXAI. It accepts text and image inputs with text output, and is suited for agentic workflows, instruction-following tasks, and applications requiring high factual...

$0.181 / 1M tokens输入$0.362 / 1M tokens输出1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Grok Build 0.1 is SpaceXAI’s fast coding model trained specifically for agentic software engineering workflows. It supports text and image inputs with text output, and is optimized for interactive coding...

$0.188 / 1M tokens输入$0.376 / 1M tokens输出256k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...

$0.027 / 1M tokens输入$0.054 / 1M tokens输出1.1M上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro....

$0.082 / 1M tokens输入$0.165 / 1M tokens输出1.1M上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly...

$0.114 / 1M tokens输入$0.414 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter...

$0.025 / 1M tokens输入$0.161 / 1M tokens输出131.1k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding,...

$0.114 / 1M tokens输入$0.34 / 1M tokens输出65.5k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...

$0.081 / 1M tokens输入$0.328 / 1M tokens输出204.8k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts...

$0.058 / 1M tokens输入$0.169 / 1M tokens输出131.1k上下文
适用场景图像理解, multimodal chat
路由已配置
流式输出工具调用JSON 模式视觉长上下文
平台整理NextModel gateway catalog (Go origin)
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OpenRouter目录

GLM-4.7 is Z.ai’s latest flagship model, featuring upgrades in two key areas: enhanced programming capabilities and more stable multi-step reasoning/execution. It demonstrates significant improvements in executing complex agent tasks while...

$0.075 / 1M tokens输入$0.33 / 1M tokens输出204.8k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...

$0.012 / 1M tokens输入$0.075 / 1M tokens输出202.8k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

GLM-5 is Z.ai’s flagship open-source foundation model engineered for complex systems design and long-horizon agent workflows. Built for expert developers, it delivers production-grade performance on large-scale programming tasks, rivaling leading...

$0.114 / 1M tokens输入$0.362 / 1M tokens输出204.8k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

GLM-5 Turbo is a new model from Z.ai designed for fast inference and strong performance in agent-driven environments such as OpenClaw scenarios. It is deeply optimized for real-world agent workflows...

$0.226 / 1M tokens输入$0.752 / 1M tokens输出202.8k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interactions, GLM-5.1 can work independently and continuously on...

$0.185 / 1M tokens输入$0.58 / 1M tokens输出204.8k上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情
OpenRouter目录

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...

$0.226 / 1M tokens输入$0.773 / 1M tokens输出1M上下文
适用场景General chat via OpenRouter, API workloads
路由已配置
流式输出工具调用JSON 模式长上下文
平台整理NextModel gateway catalog (Go origin)
查看详情

决策表

一屏看完价格、上下文、能力、状态与来源。

适合在进入生产测试、成本估算或提供方策略决策前快速缩小候选范围。

模型提供方输入输出上下文能力适用场景延迟状态来源
Anthropic: Claude Fable Latest~anthropic/claude-fable-latestOpenRouter$1.88 / 1M tokens$9.40 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic Claude Haiku Latest~anthropic/claude-haiku-latestOpenRouter$0.188 / 1M tokens$0.94 / 1M tokens200k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Opus Latest~anthropic/claude-opus-latestOpenRouter$0.94 / 1M tokens$4.70 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic Claude Sonnet Latest~anthropic/claude-sonnet-latestOpenRouter$0.564 / 1M tokens$2.82 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google Gemini Flash Latest~google/gemini-flash-latestOpenRouter$0.282 / 1M tokens$1.69 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google Gemini Pro Latest~google/gemini-pro-latestOpenRouter$0.376 / 1M tokens$2.26 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
MoonshotAI Kimi Latest~moonshotai/kimi-latestOpenRouter$0.124 / 1M tokens$0.658 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI GPT Latest~openai/gpt-latestOpenRouter$0.94 / 1M tokens$5.64 / 1M tokens1.1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI GPT Mini Latest~openai/gpt-mini-latestOpenRouter$0.142 / 1M tokens$0.846 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
AI21: Jamba Large 1.7ai21/jamba-large-1.7OpenRouter$0.376 / 1M tokens$1.50 / 1M tokens256k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Aion 1.0aion-labs/aion-1.0OpenRouter$0.752 / 1M tokens$1.50 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Aion 1.0 Miniaion-labs/aion-1.0-miniOpenRouter$0.132 / 1M tokens$0.263 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
AionLabs: Aion-2.0aion-labs/aion-2.0OpenRouter$0.152 / 1M tokens$0.302 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
AionLabs: Aion-RP 1.0 (8B)aion-labs/aion-rp-llama-3.1-8bOpenRouter$0.152 / 1M tokens$0.302 / 1M tokens32.8k
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
AllenAI: Olmo 3 32B Thinkallenai/olmo-3-32b-thinkOpenRouter$0.029 / 1M tokens$0.094 / 1M tokens65.5k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Amazon: Nova 2 Liteamazon/nova-2-lite-v1OpenRouter$0.058 / 1M tokens$0.47 / 1M tokens1M
流式输出工具调用视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Amazon: Nova Lite 1.0amazon/nova-lite-v1OpenRouter$0.012 / 1M tokens$0.046 / 1M tokens300k
流式输出工具调用视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Amazon: Nova Micro 1.0amazon/nova-micro-v1OpenRouter$0.0072 / 1M tokens$0.027 / 1M tokens128k
流式输出工具调用长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Amazon: Nova Premier 1.0amazon/nova-premier-v1OpenRouter$0.47 / 1M tokens$2.35 / 1M tokens1M
流式输出工具调用视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Amazon: Nova Pro 1.0amazon/nova-pro-v1OpenRouter$0.152 / 1M tokens$0.602 / 1M tokens300k
流式输出工具调用视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Magnum v4 72Banthracite-org/magnum-v4-72bOpenRouter$0.564 / 1M tokens$0.94 / 1M tokens16.4k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Anthropic: Claude 3 Haikuanthropic/claude-3-haikuAnthropic$0.048 / 1M tokens$0.236 / 1M tokens200k
流式输出工具调用视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Claude 3.5 Haikuanthropic/claude-3.5-haikuAnthropic$0.152 / 1M tokens$0.752 / 1M tokens
流式输出
General chat via Anthropic, API workloads1000-3000ms目录平台整理
Anthropic: Claude Fable 5anthropic/claude-fable-5Anthropic$1.45 / 1M tokens$7.23 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Haiku 4.5anthropic/claude-haiku-4.5Anthropic$0.145 / 1M tokens$0.723 / 1M tokens200k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Opus 4anthropic/claude-opus-4Anthropic$2.82 / 1M tokens$14.11 / 1M tokens200k
流式输出工具调用视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Opus 4.1anthropic/claude-opus-4.1Anthropic$2.82 / 1M tokens$14.11 / 1M tokens200k
流式输出工具调用视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Opus 4.5anthropic/claude-opus-4.5Anthropic$0.723 / 1M tokens$3.62 / 1M tokens200k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Opus 4.6anthropic/claude-opus-4.6Anthropic$0.723 / 1M tokens$3.62 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Claude Opus 4.6 Fastanthropic/claude-opus-4.6-fastAnthropic$5.64 / 1M tokens$28.21 / 1M tokens
流式输出
General chat via Anthropic, API workloads1000-3000ms目录平台整理
Anthropic: Claude Opus 4.7anthropic/claude-opus-4.7Anthropic$0.723 / 1M tokens$3.62 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Opus 4.7 (Fast)anthropic/claude-opus-4.7-fastAnthropic$5.64 / 1M tokens$28.21 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Opus 4.8anthropic/claude-opus-4.8Anthropic$0.723 / 1M tokens$3.62 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Opus 4.8 (Fast)anthropic/claude-opus-4.8-fastAnthropic$1.88 / 1M tokens$9.40 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Sonnet 4anthropic/claude-sonnet-4Anthropic$0.564 / 1M tokens$2.82 / 1M tokens1M
流式输出工具调用视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Sonnet 4.5anthropic/claude-sonnet-4.5Anthropic$0.434 / 1M tokens$2.17 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Anthropic: Claude Sonnet 4.6anthropic/claude-sonnet-4.6Anthropic$0.434 / 1M tokens$2.17 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Coder Largearcee-ai/coder-largeOpenRouter$0.094 / 1M tokens$0.152 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Arcee AI: Trinity Large Thinkingarcee-ai/trinity-large-thinkingOpenRouter$0.048 / 1M tokens$0.152 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Trinity Miniarcee-ai/trinity-miniOpenRouter$0.0087 / 1M tokens$0.029 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Arcee AI: Virtuoso Largearcee-ai/virtuoso-largeOpenRouter$0.142 / 1M tokens$0.226 / 1M tokens131.1k
流式输出工具调用长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Baidu: ERNIE 4.5 VL 424B A47B baidu/ernie-4.5-vl-424b-a47bOpenRouter$0.08 / 1M tokens$0.236 / 1M tokens123k
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
ByteDance Seed: Seed 1.6bytedance-seed/seed-1.6OpenRouter$0.048 / 1M tokens$0.376 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
ByteDance Seed: Seed 1.6 Flashbytedance-seed/seed-1.6-flashOpenRouter$0.014 / 1M tokens$0.058 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
ByteDance Seed: Seed-2.0-Litebytedance-seed/seed-2.0-liteOpenRouter$0.048 / 1M tokens$0.376 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
ByteDance Seed: Seed-2.0-Minibytedance-seed/seed-2.0-miniOpenRouter$0.02 / 1M tokens$0.075 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
ByteDance: UI-TARS 7B bytedance/ui-tars-1.5-7bByteDance Seed$0.02 / 1M tokens$0.038 / 1M tokens128k
流式输出视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Cohere: Command Acohere/command-aOpenRouter$0.47 / 1M tokens$1.88 / 1M tokens256k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Cohere: Command R (08-2024)cohere/command-r-08-2024OpenRouter$0.029 / 1M tokens$0.114 / 1M tokens128k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Cohere: Command R+ (08-2024)cohere/command-r-plus-08-2024OpenRouter$0.47 / 1M tokens$1.88 / 1M tokens128k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Cohere: Command R7B (12-2024)cohere/command-r7b-12-2024OpenRouter$0.0072 / 1M tokens$0.029 / 1M tokens128k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Deep Cogito: Cogito v2.1 671Bdeepcogito/cogito-v2.1-671bOpenRouter$0.236 / 1M tokens$0.236 / 1M tokens128k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Deepseek V4 Flashdeepseek-v4-flashDeepSeek$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
Deepseek V4 PROdeepseek-v4-proDeepSeek$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: DeepSeek V3deepseek/deepseek-chatDeepSeek$0.038 / 1M tokens$0.152 / 1M tokens163.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: DeepSeek V3 0324deepseek/deepseek-chat-v3-0324DeepSeek$0.038 / 1M tokens$0.146 / 1M tokens163.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: DeepSeek V3.1deepseek/deepseek-chat-v3.1DeepSeek$0.041 / 1M tokens$0.149 / 1M tokens163.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: R1deepseek/deepseek-r1DeepSeek$0.132 / 1M tokens$0.47 / 1M tokens163.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: R1 0528deepseek/deepseek-r1-0528DeepSeek$0.094 / 1M tokens$0.405 / 1M tokens163.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: R1 Distill Llama 70Bdeepseek/deepseek-r1-distill-llama-70bDeepSeek$0.152 / 1M tokens$0.152 / 1M tokens8.2k
流式输出
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: DeepSeek V3.1 Terminusdeepseek/deepseek-v3.1-terminusDeepSeek$0.052 / 1M tokens$0.179 / 1M tokens163.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: DeepSeek V3.2deepseek/deepseek-v3.2DeepSeek$0.043 / 1M tokens$0.065 / 1M tokens163.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: DeepSeek V3.2 Expdeepseek/deepseek-v3.2-expDeepSeek$0.052 / 1M tokens$0.078 / 1M tokens163.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: DeepSeek V4 Flash 0423deepseek/deepseek-v4-flashDeepSeek$0.017 / 1M tokens$0.035 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
DeepSeek: DeepSeek V4 Prodeepseek/deepseek-v4-proDeepSeek$0.082 / 1M tokens$0.165 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
Doubao Seed 2 0 Codedoubao-seed-2-0-codeVolcengine$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
Doubao Seed 2 0 Litedoubao-seed-2-0-liteVolcengine$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
Doubao Seed 2 0 Minidoubao-seed-2-0-miniVolcengine$0.0043 / 1M tokens$0.041 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
Doubao Seed 2 0 PROdoubao-seed-2-0-proVolcengine$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
Doubao Seedance 1 0 PROdoubao-seedance-1-0-proVolcengine$0 / 1M tokens$0 / 1M tokens
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Doubao Seedance 1 5 PROdoubao-seedance-1-5-proVolcengine$0 / 1M tokens$0 / 1M tokens
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Doubao Seedance 2 0doubao-seedance-2-0Volcengine$0 / 1M tokens$0 / 1M tokens
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Doubao Seedance 2 0 Fastdoubao-seedance-2-0-fastVolcengine$0 / 1M tokens$0 / 1M tokens
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Doubao Seedance 2 0 Minidoubao-seedance-2-0-miniVolcengine$0 / 1M tokens$0 / 1M tokens
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Doubao Seedream 4 0doubao-seedream-4-0Volcengine$0 / 1M tokens$0 / 1M tokens
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Doubao Seedream 4 5doubao-seedream-4-5Volcengine$0 / 1M tokens$0 / 1M tokens
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Doubao Seedream 5 0doubao-seedream-5-0Volcengine$0 / 1M tokens$0 / 1M tokens
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Doubao Seedream 5 0 PROdoubao-seedream-5-0-proVolcengine$0 / 1M tokens$0 / 1M tokens
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
RNJ 1 Instructessentialai/rnj-1-instructOpenRouter$0.029 / 1M tokens$0.029 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
GLM 5 2glm-5-2Zhipu AI (GLM)$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
Google: Gemini 2.5 Flashgoogle/gemini-2.5-flashGoogle$0.043 / 1M tokens$0.362 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Nano Banana (Gemini 2.5 Flash Image)google/gemini-2.5-flash-imageGoogle$0.058 / 1M tokens$0.47 / 1M tokens32.8k
流式输出JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemini 2.5 Flash Litegoogle/gemini-2.5-flash-liteGoogle$0.02 / 1M tokens$0.075 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Gemini 2.5 Flash Lite Preview 09 2025google/gemini-2.5-flash-lite-preview-09-2025Google$0.02 / 1M tokens$0.075 / 1M tokens
流式输出
General chat via Google, API workloads1000-3000ms目录平台整理
Google: Gemini 2.5 Progoogle/gemini-2.5-proGoogle$0.236 / 1M tokens$1.88 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemini 2.5 Pro Preview 06-05google/gemini-2.5-pro-previewGoogle$0.236 / 1M tokens$1.88 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemini 2.5 Pro Preview 05-06google/gemini-2.5-pro-preview-05-06Google$0.236 / 1M tokens$1.88 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemini 3 Flash Previewgoogle/gemini-3-flash-previewGoogle$0.072 / 1M tokens$0.434 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Nano Banana Pro (Gemini 3 Pro Image)google/gemini-3-pro-imageGoogle$0.376 / 1M tokens$2.26 / 1M tokens131.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Nano Banana Pro (Gemini 3 Pro Image Preview)google/gemini-3-pro-image-previewGoogle$0.376 / 1M tokens$2.26 / 1M tokens65.5k
流式输出JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Nano Banana 2 (Gemini 3.1 Flash Image)google/gemini-3.1-flash-imageGoogle$0.094 / 1M tokens$0.564 / 1M tokens131.1k
流式输出JSON 模式视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Nano Banana 2 (Gemini 3.1 Flash Image Preview)google/gemini-3.1-flash-image-previewGoogle$0.094 / 1M tokens$0.564 / 1M tokens65.5k
流式输出JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemini 3.1 Flash Litegoogle/gemini-3.1-flash-liteGoogle$0.036 / 1M tokens$0.217 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-previewGoogle$0.048 / 1M tokens$0.282 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemini 3.1 Pro Previewgoogle/gemini-3.1-pro-previewGoogle$0.376 / 1M tokens$2.26 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemini 3.1 Pro Preview Custom Toolsgoogle/gemini-3.1-pro-preview-customtoolsGoogle$0.376 / 1M tokens$2.26 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemini 3.5 Flashgoogle/gemini-3.5-flashGoogle$0.217 / 1M tokens$1.30 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemma 2 27Bgoogle/gemma-2-27b-itGoogle$0.123 / 1M tokens$0.123 / 1M tokens8.2k
流式输出JSON 模式
General chat via Google, API workloads1000-3000ms目录平台整理
Google: Gemma 3 12Bgoogle/gemma-3-12b-itGoogle$0.01 / 1M tokens$0.029 / 1M tokens131.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemma 3 27Bgoogle/gemma-3-27b-itGoogle$0.016 / 1M tokens$0.03 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemma 3 4Bgoogle/gemma-3-4b-itGoogle$0.01 / 1M tokens$0.02 / 1M tokens131.1k
流式输出JSON 模式视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemma 3n 4Bgoogle/gemma-3n-e4b-itGoogle$0.012 / 1M tokens$0.023 / 1M tokens32.8k
流式输出JSON 模式
General chat via Google, API workloads1000-3000ms目录平台整理
Google: Gemma 4 26B A4B google/gemma-4-26b-a4b-itGoogle$0.012 / 1M tokens$0.062 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Google: Gemma 4 31Bgoogle/gemma-4-31b-itGoogle$0.023 / 1M tokens$0.067 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
MythoMax 13Bgryphe/mythomax-l2-13bOpenRouter$0.012 / 1M tokens$0.012 / 1M tokens8.2k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
IBM: Granite 4.0 Microibm-granite/granite-4.0-h-microOpenRouter$0.0043 / 1M tokens$0.022 / 1M tokens131k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
IBM: Granite 4.1 8Bibm-granite/granite-4.1-8bOpenRouter$0.01 / 1M tokens$0.02 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Inception: Mercury 2inception/mercury-2OpenRouter$0.048 / 1M tokens$0.142 / 1M tokens128k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
inclusionAI: Ling-2.6-1Tinclusionai/ling-2.6-1tOpenRouter$0.014 / 1M tokens$0.119 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
inclusionAI: Ling-2.6-flashinclusionai/ling-2.6-flashOpenRouter$0.0029 / 1M tokens$0.0058 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
inclusionAI: Ring-2.6-1Tinclusionai/ring-2.6-1tOpenRouter$0.014 / 1M tokens$0.119 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Inflection 3 PIinflection/inflection-3-piOpenRouter$0.47 / 1M tokens$1.88 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Inflection 3 Productivityinflection/inflection-3-productivityOpenRouter$0.47 / 1M tokens$1.88 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Kimi K2 6kimi-k2-6Moonshot AI$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
Kimi K2 7 Codekimi-k2-7-codeMoonshot AI$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
Kwaipilot: KAT-Coder-Pro V2kwaipilot/kat-coder-pro-v2OpenRouter$0.058 / 1M tokens$0.226 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
LFM 2 24b A2Bliquid/lfm-2-24b-a2bOpenRouter$0.0058 / 1M tokens$0.023 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Mancer: Weaver (alpha)mancer/weaverOpenRouter$0.142 / 1M tokens$0.188 / 1M tokens8k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Llama 3 8b Instructmeta-llama/llama-3-8b-instructOpenRouter$0.027 / 1M tokens$0.027 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Meta: Llama 3.1 70B Instructmeta-llama/llama-3.1-70b-instructOpenRouter$0.075 / 1M tokens$0.075 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Meta: Llama 3.1 8B Instructmeta-llama/llama-3.1-8b-instructOpenRouter$0.0043 / 1M tokens$0.0058 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Llama 3.2 11b Vision Instructmeta-llama/llama-3.2-11b-vision-instructOpenRouter$0.065 / 1M tokens$0.065 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Meta: Llama 3.2 1B Instructmeta-llama/llama-3.2-1b-instructOpenRouter$0.0058 / 1M tokens$0.039 / 1M tokens60k
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Meta: Llama 3.2 3B Instructmeta-llama/llama-3.2-3b-instructOpenRouter$0.01 / 1M tokens$0.064 / 1M tokens131.1k
流式输出长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Meta: Llama 3.3 70B Instructmeta-llama/llama-3.3-70b-instructOpenRouter$0.02 / 1M tokens$0.061 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Meta: Llama 4 Maverickmeta-llama/llama-4-maverickOpenRouter$0.029 / 1M tokens$0.114 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Meta: Llama 4 Scoutmeta-llama/llama-4-scoutOpenRouter$0.02 / 1M tokens$0.058 / 1M tokens1.3M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Meta: Llama Guard 4 12Bmeta-llama/llama-guard-4-12bOpenRouter$0.035 / 1M tokens$0.035 / 1M tokens1M
流式输出JSON 模式视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Microsoft: Phi 4microsoft/phi-4OpenRouter$0.013 / 1M tokens$0.027 / 1M tokens16.4k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
PHI 4 Mini Instructmicrosoft/phi-4-mini-instructOpenRouter$0.016 / 1M tokens$0.067 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
WizardLM-2 8x22Bmicrosoft/wizardlm-2-8x22bOpenRouter$0.117 / 1M tokens$0.117 / 1M tokens65.5k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Minimax M2 7minimax-m2-7MiniMax$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
Minimax M3minimax-m3MiniMax$0 / 1M tokens$0 / 1M tokens
流式输出
中文问答, general chat1000-3000ms目录平台整理
MiniMax: MiniMax-01minimax/minimax-01MiniMax$0.038 / 1M tokens$0.208 / 1M tokens1M
流式输出视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
MiniMax: MiniMax M1minimax/minimax-m1MiniMax$0.075 / 1M tokens$0.414 / 1M tokens1M
流式输出工具调用长上下文
中文问答, general chat1000-3000ms目录平台整理
MiniMax: MiniMax M2minimax/minimax-m2MiniMax$0.049 / 1M tokens$0.188 / 1M tokens204.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
MiniMax: MiniMax M2-herminimax/minimax-m2-herMiniMax$0.058 / 1M tokens$0.226 / 1M tokens65.5k
流式输出
中文问答, general chat1000-3000ms目录平台整理
MiniMax: MiniMax M2.1minimax/minimax-m2.1MiniMax$0.055 / 1M tokens$0.179 / 1M tokens204.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
MiniMax: MiniMax M2.5minimax/minimax-m2.5MiniMax$0.029 / 1M tokens$0.169 / 1M tokens204.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
MiniMax: MiniMax M2.7minimax/minimax-m2.7MiniMax$0.048 / 1M tokens$0.188 / 1M tokens204.8k
流式输出工具调用JSON 模式长上下文
中文问答, general chat1000-3000ms目录平台整理
MiniMax: MiniMax M3minimax/minimax-m3MiniMax$0.058 / 1M tokens$0.226 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Codestral 2508mistralai/codestral-2508OpenRouter$0.058 / 1M tokens$0.169 / 1M tokens256k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Devstral 2512mistralai/devstral-2512OpenRouter$0.075 / 1M tokens$0.376 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Mistral: Ministral 3 14B 2512mistralai/ministral-14b-2512OpenRouter$0.038 / 1M tokens$0.038 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Ministral 3 3B 2512mistralai/ministral-3b-2512OpenRouter$0.02 / 1M tokens$0.02 / 1M tokens131.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Ministral 3 8B 2512mistralai/ministral-8b-2512OpenRouter$0.029 / 1M tokens$0.029 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral Largemistralai/mistral-largeOpenRouter$0.376 / 1M tokens$1.13 / 1M tokens128k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Mistral Large 2407mistralai/mistral-large-2407OpenRouter$0.376 / 1M tokens$1.13 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Mistral: Mistral Large 3 2512mistralai/mistral-large-2512OpenRouter$0.094 / 1M tokens$0.282 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Mistral Medium 3mistralai/mistral-medium-3OpenRouter$0.075 / 1M tokens$0.376 / 1M tokens131.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Mistral Medium 3.5mistralai/mistral-medium-3-5OpenRouter$0.282 / 1M tokens$1.41 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Mistral Medium 3.1mistralai/mistral-medium-3.1OpenRouter$0.075 / 1M tokens$0.376 / 1M tokens131.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Mistral Nemomistralai/mistral-nemoOpenRouter$0.0043 / 1M tokens$0.0058 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Mistral: Sabamistralai/mistral-sabaOpenRouter$0.038 / 1M tokens$0.114 / 1M tokens32.8k
流式输出工具调用JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Mistral: Mistral Small 3mistralai/mistral-small-24b-instruct-2501OpenRouter$0.01 / 1M tokens$0.016 / 1M tokens32.8k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Mistral: Mistral Small 4mistralai/mistral-small-2603OpenRouter$0.029 / 1M tokens$0.114 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Mistral Small 3.1 24Bmistralai/mistral-small-3.1-24b-instructOpenRouter$0.067 / 1M tokens$0.106 / 1M tokens128k
流式输出视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Mistral Small 3.2 24Bmistralai/mistral-small-3.2-24b-instructOpenRouter$0.014 / 1M tokens$0.038 / 1M tokens256k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Mistral: Mixtral 8x22B Instructmistralai/mixtral-8x22b-instructOpenRouter$0.376 / 1M tokens$1.13 / 1M tokens65.5k
流式输出工具调用JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Mistral: Voxtral Small 24B 2507mistralai/voxtral-small-24b-2507OpenRouter$0.02 / 1M tokens$0.058 / 1M tokens32k
流式输出工具调用JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
MoonshotAI: Kimi K2 0711moonshotai/kimi-k2OpenRouter$0.109 / 1M tokens$0.434 / 1M tokens131.1k
流式输出工具调用长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
MoonshotAI: Kimi K2 0905moonshotai/kimi-k2-0905OpenRouter$0.114 / 1M tokens$0.47 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
MoonshotAI: Kimi K2 Thinkingmoonshotai/kimi-k2-thinkingOpenRouter$0.114 / 1M tokens$0.47 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
MoonshotAI: Kimi K2.5moonshotai/kimi-k2.5OpenRouter$0.071 / 1M tokens$0.382 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
MoonshotAI: Kimi K2.6moonshotai/kimi-k2.6OpenRouter$0.124 / 1M tokens$0.658 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
MoonshotAI: Kimi K2.7 Codemoonshotai/kimi-k2.7-codeOpenRouter$0.116 / 1M tokens$0.579 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Morph: Morph V3 Fastmorph/morph-v3-fastOpenRouter$0.152 / 1M tokens$0.226 / 1M tokens81.9k
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Morph: Morph V3 Largemorph/morph-v3-largeOpenRouter$0.169 / 1M tokens$0.357 / 1M tokens262.1k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Nous: Hermes 3 405B Instructnousresearch/hermes-3-llama-3.1-405bOpenRouter$0.188 / 1M tokens$0.188 / 1M tokens131.1k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Nous: Hermes 3 70B Instructnousresearch/hermes-3-llama-3.1-70bOpenRouter$0.132 / 1M tokens$0.132 / 1M tokens131.1k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Nous: Hermes 4 405Bnousresearch/hermes-4-405bOpenRouter$0.188 / 1M tokens$0.564 / 1M tokens131.1k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Nous: Hermes 4 70Bnousresearch/hermes-4-70bOpenRouter$0.025 / 1M tokens$0.075 / 1M tokens131.1k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Llama 3.3 Nemotron Super 49b V1.5nvidia/llama-3.3-nemotron-super-49b-v1.5OpenRouter$0.075 / 1M tokens$0.075 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
NVIDIA: Nemotron 3 Nano 30B A3Bnvidia/nemotron-3-nano-30b-a3bOpenRouter$0.01 / 1M tokens$0.038 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
NVIDIA: Nemotron 3 Supernvidia/nemotron-3-super-120b-a12bOpenRouter$0.017 / 1M tokens$0.085 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
NVIDIA: Nemotron 3 Ultranvidia/nemotron-3-ultra-550b-a55bOpenRouter$0.094 / 1M tokens$0.414 / 1M tokens512.3k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
OpenAI: GPT-3.5 Turboopenai/gpt-3.5-turboOpenAI$0.094 / 1M tokens$0.282 / 1M tokens16.4k
流式输出工具调用JSON 模式
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT-3.5 Turbo (older v0613)openai/gpt-3.5-turbo-0613OpenAI$0.188 / 1M tokens$0.376 / 1M tokens4.1k
流式输出工具调用JSON 模式
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT-3.5 Turbo 16kopenai/gpt-3.5-turbo-16kOpenAI$0.564 / 1M tokens$0.752 / 1M tokens16.4k
流式输出工具调用JSON 模式
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT-3.5 Turbo Instructopenai/gpt-3.5-turbo-instructOpenAI$0.282 / 1M tokens$0.376 / 1M tokens4.1k
流式输出JSON 模式
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT-4openai/gpt-4OpenAI$5.64 / 1M tokens$11.28 / 1M tokens8.2k
流式输出工具调用JSON 模式
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT-4 Turboopenai/gpt-4-turboOpenAI$1.88 / 1M tokens$5.64 / 1M tokens128k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-4 Turbo Previewopenai/gpt-4-turbo-previewOpenAI$1.88 / 1M tokens$5.64 / 1M tokens128k
流式输出工具调用JSON 模式长上下文
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT-4.1openai/gpt-4.1OpenAI$0.289 / 1M tokens$1.16 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-4.1 Miniopenai/gpt-4.1-miniOpenAI$0.058 / 1M tokens$0.231 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-4.1 Nanoopenai/gpt-4.1-nanoOpenAI$0.014 / 1M tokens$0.058 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-4oopenai/gpt-4oOpenAI$0.362 / 1M tokens$1.45 / 1M tokens128k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-4o (2024-05-13)openai/gpt-4o-2024-05-13OpenAI$0.94 / 1M tokens$2.82 / 1M tokens128k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-4o (2024-08-06)openai/gpt-4o-2024-08-06OpenAI$0.47 / 1M tokens$1.88 / 1M tokens128k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-4o (2024-11-20)openai/gpt-4o-2024-11-20OpenAI$0.47 / 1M tokens$1.88 / 1M tokens128k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-4o-miniopenai/gpt-4o-miniOpenAI$0.022 / 1M tokens$0.087 / 1M tokens128k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-4o-mini (2024-07-18)openai/gpt-4o-mini-2024-07-18OpenAI$0.029 / 1M tokens$0.114 / 1M tokens128k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
GPT 4o Mini Search Previewopenai/gpt-4o-mini-search-previewOpenAI$0.029 / 1M tokens$0.114 / 1M tokens
流式输出
General chat via OpenAI, API workloads1000-3000ms目录平台整理
GPT 4o Search Previewopenai/gpt-4o-search-previewOpenAI$0.47 / 1M tokens$1.88 / 1M tokens
流式输出
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT-5openai/gpt-5OpenAI$0.181 / 1M tokens$1.45 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
GPT 5 Chatopenai/gpt-5-chatOpenAI$0.236 / 1M tokens$1.88 / 1M tokens
流式输出
General chat via OpenAI, API workloads1000-3000ms目录平台整理
GPT 5 Codexopenai/gpt-5-codexOpenAI$0.236 / 1M tokens$1.88 / 1M tokens
流式输出
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT-5 Imageopenai/gpt-5-imageOpenAI$1.88 / 1M tokens$1.88 / 1M tokens400k
流式输出JSON 模式视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5 Image Miniopenai/gpt-5-image-miniOpenAI$0.47 / 1M tokens$0.376 / 1M tokens400k
流式输出JSON 模式视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5 Miniopenai/gpt-5-miniOpenAI$0.036 / 1M tokens$0.289 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5 Nanoopenai/gpt-5-nanoOpenAI$0.0072 / 1M tokens$0.058 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5 Proopenai/gpt-5-proOpenAI$2.82 / 1M tokens$22.57 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.1openai/gpt-5.1OpenAI$0.181 / 1M tokens$1.45 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
GPT 5.1 Chatopenai/gpt-5.1-chatOpenAI$0.236 / 1M tokens$1.88 / 1M tokens
流式输出
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT-5.1-Codexopenai/gpt-5.1-codexOpenAI$0.236 / 1M tokens$1.88 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.1-Codex-Maxopenai/gpt-5.1-codex-maxOpenAI$0.236 / 1M tokens$1.88 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.1-Codex-Miniopenai/gpt-5.1-codex-miniOpenAI$0.048 / 1M tokens$0.376 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.2openai/gpt-5.2OpenAI$0.253 / 1M tokens$2.03 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.2 Chatopenai/gpt-5.2-chatOpenAI$0.33 / 1M tokens$2.63 / 1M tokens128k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.2-Codexopenai/gpt-5.2-codexOpenAI$0.33 / 1M tokens$2.63 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.2 Proopenai/gpt-5.2-proOpenAI$3.95 / 1M tokens$31.60 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.3 Chatopenai/gpt-5.3-chatOpenAI$0.33 / 1M tokens$2.63 / 1M tokens128k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.3-Codexopenai/gpt-5.3-codexOpenAI$0.33 / 1M tokens$2.63 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.4openai/gpt-5.4OpenAI$0.47 / 1M tokens$2.82 / 1M tokens1.1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.4 Image 2openai/gpt-5.4-image-2OpenAI$1.50 / 1M tokens$2.82 / 1M tokens272k
流式输出JSON 模式视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.4 Miniopenai/gpt-5.4-miniOpenAI$0.109 / 1M tokens$0.651 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.4 Nanoopenai/gpt-5.4-nanoOpenAI$0.029 / 1M tokens$0.181 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.4 Proopenai/gpt-5.4-proOpenAI$5.64 / 1M tokens$33.85 / 1M tokens1.1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.5openai/gpt-5.5OpenAI$0.94 / 1M tokens$5.64 / 1M tokens1.1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT-5.5 Proopenai/gpt-5.5-proOpenAI$5.64 / 1M tokens$33.85 / 1M tokens1.1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: GPT Audioopenai/gpt-audioOpenAI$0.47 / 1M tokens$1.88 / 1M tokens128k
流式输出工具调用JSON 模式长上下文
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT Audio Miniopenai/gpt-audio-miniOpenAI$0.114 / 1M tokens$0.451 / 1M tokens128k
流式输出工具调用JSON 模式长上下文
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: GPT Chat Latestopenai/gpt-chat-latestOpenAI$0.94 / 1M tokens$5.64 / 1M tokens400k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: gpt-oss-120bopenai/gpt-oss-120bOpenAI$0.0087 / 1M tokens$0.035 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: gpt-oss-20bopenai/gpt-oss-20bOpenAI$0.0058 / 1M tokens$0.027 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: gpt-oss-safeguard-20bopenai/gpt-oss-safeguard-20bOpenAI$0.014 / 1M tokens$0.058 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: o1openai/o1OpenAI$2.82 / 1M tokens$11.28 / 1M tokens200k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: o1-proopenai/o1-proOpenAI$28.21 / 1M tokens$112.85 / 1M tokens200k
流式输出JSON 模式视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: o3openai/o3OpenAI$0.289 / 1M tokens$1.16 / 1M tokens200k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
O3 Deep Researchopenai/o3-deep-researchOpenAI$1.88 / 1M tokens$7.52 / 1M tokens
流式输出
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: o3 Miniopenai/o3-miniOpenAI$0.208 / 1M tokens$0.828 / 1M tokens200k
流式输出工具调用JSON 模式长上下文
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: o3 Mini Highopenai/o3-mini-highOpenAI$0.208 / 1M tokens$0.828 / 1M tokens200k
流式输出工具调用JSON 模式长上下文
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: o3 Proopenai/o3-proOpenAI$3.76 / 1M tokens$15.05 / 1M tokens200k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
OpenAI: o4 Miniopenai/o4-miniOpenAI$0.159 / 1M tokens$0.637 / 1M tokens200k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
O4 Mini Deep Researchopenai/o4-mini-deep-researchOpenAI$0.376 / 1M tokens$1.50 / 1M tokens
流式输出
General chat via OpenAI, API workloads1000-3000ms目录平台整理
OpenAI: o4 Mini Highopenai/o4-mini-highOpenAI$0.208 / 1M tokens$0.828 / 1M tokens200k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Perceptron: Perceptron Mk1perceptron/perceptron-mk1OpenRouter$0.029 / 1M tokens$0.282 / 1M tokens32.8k
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Perplexity: Sonarperplexity/sonarOpenRouter$0.188 / 1M tokens$0.188 / 1M tokens127.1k
流式输出视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Perplexity: Sonar Deep Researchperplexity/sonar-deep-researchOpenRouter$0.376 / 1M tokens$1.50 / 1M tokens128k
流式输出长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Perplexity: Sonar Properplexity/sonar-proOpenRouter$0.564 / 1M tokens$2.82 / 1M tokens200k
流式输出视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Perplexity: Sonar Pro Searchperplexity/sonar-pro-searchOpenRouter$0.564 / 1M tokens$2.82 / 1M tokens200k
流式输出视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Perplexity: Sonar Reasoning Properplexity/sonar-reasoning-proOpenRouter$0.376 / 1M tokens$1.50 / 1M tokens128k
流式输出视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Laguna M.1poolside/laguna-m.1OpenRouter$0.038 / 1M tokens$0.075 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Laguna Xs.2poolside/laguna-xs.2OpenRouter$0.02 / 1M tokens$0.038 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Intellect 3prime-intellect/intellect-3OpenRouter$0.038 / 1M tokens$0.208 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen2.5 72B Instructqwen/qwen-2.5-72b-instructOpenRouter$0.068 / 1M tokens$0.075 / 1M tokens32.8k
流式输出工具调用JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen2.5 7B Instructqwen/qwen-2.5-7b-instructOpenRouter$0.0087 / 1M tokens$0.02 / 1M tokens32.8k
流式输出工具调用JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen2.5 Coder 32B Instructqwen/qwen-2.5-coder-32b-instructOpenRouter$0.124 / 1M tokens$0.188 / 1M tokens32.8k
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen-Plusqwen/qwen-plusOpenRouter$0.049 / 1M tokens$0.148 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen Plus 0728qwen/qwen-plus-2025-07-28OpenRouter$0.049 / 1M tokens$0.148 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen Plus 0728 (thinking)qwen/qwen-plus-2025-07-28:thinkingOpenRouter$0.049 / 1M tokens$0.148 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen2.5 VL 72B Instructqwen/qwen2.5-vl-72b-instructOpenRouter$0.152 / 1M tokens$0.188 / 1M tokens128k
流式输出JSON 模式视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3 14Bqwen/qwen3-14bOpenRouter$0.02 / 1M tokens$0.046 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22bOpenRouter$0.087 / 1M tokens$0.343 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507OpenRouter$0.017 / 1M tokens$0.02 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507OpenRouter$0.02 / 1M tokens$0.02 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 30B A3Bqwen/qwen3-30b-a3bOpenRouter$0.023 / 1M tokens$0.094 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 30B A3B Instruct 2507qwen/qwen3-30b-a3b-instruct-2507OpenRouter$0.01 / 1M tokens$0.038 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 30B A3B Thinking 2507qwen/qwen3-30b-a3b-thinking-2507OpenRouter$0.016 / 1M tokens$0.075 / 1M tokens81.9k
流式输出工具调用JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 32Bqwen/qwen3-32bOpenRouter$0.016 / 1M tokens$0.054 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 8Bqwen/qwen3-8bOpenRouter$0.01 / 1M tokens$0.075 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 Coder 480B A35Bqwen/qwen3-coderOpenRouter$0.042 / 1M tokens$0.34 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instructOpenRouter$0.014 / 1M tokens$0.052 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 Coder Flashqwen/qwen3-coder-flashOpenRouter$0.038 / 1M tokens$0.184 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 Coder Nextqwen/qwen3-coder-nextOpenRouter$0.022 / 1M tokens$0.152 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 Coder Plusqwen/qwen3-coder-plusOpenRouter$0.123 / 1M tokens$0.612 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 Maxqwen/qwen3-maxOpenRouter$0.148 / 1M tokens$0.734 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 Max Thinkingqwen/qwen3-max-thinkingOpenRouter$0.148 / 1M tokens$0.734 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 Next 80B A3B Instructqwen/qwen3-next-80b-a3b-instructOpenRouter$0.017 / 1M tokens$0.208 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 Next 80B A3B Thinkingqwen/qwen3-next-80b-a3b-thinkingOpenRouter$0.019 / 1M tokens$0.148 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3 VL 235B A22B Instructqwen/qwen3-vl-235b-a22b-instructOpenRouter$0.038 / 1M tokens$0.166 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3 VL 235B A22B Thinkingqwen/qwen3-vl-235b-a22b-thinkingOpenRouter$0.049 / 1M tokens$0.49 / 1M tokens131.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3 VL 30B A3B Instructqwen/qwen3-vl-30b-a3b-instructOpenRouter$0.025 / 1M tokens$0.098 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3 VL 30B A3B Thinkingqwen/qwen3-vl-30b-a3b-thinkingOpenRouter$0.025 / 1M tokens$0.294 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3 VL 32B Instructqwen/qwen3-vl-32b-instructOpenRouter$0.02 / 1M tokens$0.08 / 1M tokens131.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3 VL 8B Instructqwen/qwen3-vl-8b-instructOpenRouter$0.016 / 1M tokens$0.094 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3 VL 8B Thinkingqwen/qwen3-vl-8b-thinkingOpenRouter$0.023 / 1M tokens$0.258 / 1M tokens131.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.5-122B-A10Bqwen/qwen3.5-122b-a10bOpenRouter$0.049 / 1M tokens$0.392 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.5-27Bqwen/qwen3.5-27bOpenRouter$0.038 / 1M tokens$0.294 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.5-35B-A3Bqwen/qwen3.5-35b-a3bOpenRouter$0.027 / 1M tokens$0.188 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.5 397B A17Bqwen/qwen3.5-397b-a17bOpenRouter$0.072 / 1M tokens$0.462 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.5-9Bqwen/qwen3.5-9bOpenRouter$0.02 / 1M tokens$0.029 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.5-Flashqwen/qwen3.5-flash-02-23OpenRouter$0.013 / 1M tokens$0.049 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.5 Plus 2026-02-15qwen/qwen3.5-plus-02-15OpenRouter$0.049 / 1M tokens$0.294 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.5 Plus 2026-04-20qwen/qwen3.5-plus-20260420OpenRouter$0.058 / 1M tokens$0.34 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.6 27Bqwen/qwen3.6-27bOpenRouter$0.055 / 1M tokens$0.598 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.6 35B A3Bqwen/qwen3.6-35b-a3bOpenRouter$0.027 / 1M tokens$0.188 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.6 Flashqwen/qwen3.6-flashOpenRouter$0.036 / 1M tokens$0.213 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.6 Max Previewqwen/qwen3.6-max-previewOpenRouter$0.197 / 1M tokens$1.17 / 1M tokens262.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3.6 Plusqwen/qwen3.6-plusOpenRouter$0.062 / 1M tokens$0.367 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Qwen: Qwen3.7 Maxqwen/qwen3.7-maxOpenRouter$0.236 / 1M tokens$0.706 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Qwen: Qwen3.7 Plusqwen/qwen3.7-plusOpenRouter$0.061 / 1M tokens$0.242 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Reka Edgerekaai/reka-edgeOpenRouter$0.02 / 1M tokens$0.02 / 1M tokens16.4k
流式输出工具调用视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Reka Flash 3rekaai/reka-flash-3OpenRouter$0.02 / 1M tokens$0.038 / 1M tokens65.5k
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Relace: Relace Apply 3relace/relace-apply-3OpenRouter$0.161 / 1M tokens$0.236 / 1M tokens256k
流式输出长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Relace: Relace Searchrelace/relace-searchOpenRouter$0.188 / 1M tokens$0.564 / 1M tokens256k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Sao10K: Llama 3 8B Lunarissao10k/l3-lunaris-8bOpenRouter$0.0087 / 1M tokens$0.01 / 1M tokens8.2k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
L3.1 70b Hanami X1sao10k/l3.1-70b-hanami-x1OpenRouter$0.564 / 1M tokens$0.564 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Sao10K: Llama 3.1 Euryale 70B v2.2sao10k/l3.1-euryale-70bOpenRouter$0.161 / 1M tokens$0.161 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Sao10K: Llama 3.3 Euryale 70Bsao10k/l3.3-euryale-70bOpenRouter$0.123 / 1M tokens$0.142 / 1M tokens131.1k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
StepFun: Step 3.5 Flashstepfun/step-3.5-flashOpenRouter$0.017 / 1M tokens$0.058 / 1M tokens262.1k
流式输出工具调用长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
StepFun: Step 3.7 Flashstepfun/step-3.7-flashOpenRouter$0.038 / 1M tokens$0.217 / 1M tokens262.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Routerswitchpoint/routerOpenRouter$0.161 / 1M tokens$0.639 / 1M tokens
流式输出
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Tencent: Hunyuan A13B Instructtencent/hunyuan-a13b-instructOpenRouter$0.027 / 1M tokens$0.109 / 1M tokens131.1k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Tencent: Hy3 previewtencent/hy3-previewOpenRouter$0.013 / 1M tokens$0.041 / 1M tokens262.1k
流式输出工具调用长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
TheDrummer: Cydonia 24B V4.1thedrummer/cydonia-24b-v4.1OpenRouter$0.058 / 1M tokens$0.094 / 1M tokens131.1k
流式输出JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
TheDrummer: Rocinante 12Bthedrummer/rocinante-12bOpenRouter$0.033 / 1M tokens$0.081 / 1M tokens65.5k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
TheDrummer: Skyfall 36B V2thedrummer/skyfall-36b-v2OpenRouter$0.104 / 1M tokens$0.152 / 1M tokens32.8k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
TheDrummer: UnslopNemo 12Bthedrummer/unslopnemo-12bOpenRouter$0.075 / 1M tokens$0.075 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
ReMM SLERP 13Bundi95/remm-slerp-l2-13bOpenRouter$0.085 / 1M tokens$0.123 / 1M tokens6.1k
流式输出JSON 模式
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Upstage: Solar Pro 3upstage/solar-pro-3OpenRouter$0.029 / 1M tokens$0.114 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Writer: Palmyra X5writer/palmyra-x5OpenRouter$0.114 / 1M tokens$1.13 / 1M tokens1M
流式输出长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
SpaceXAI: Grok 4.20x-ai/grok-4.20OpenRouter$0.236 / 1M tokens$0.47 / 1M tokens2M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
SpaceXAI: Grok 4.20 Multi-Agentx-ai/grok-4.20-multi-agentOpenRouter$0.236 / 1M tokens$0.47 / 1M tokens2M
流式输出JSON 模式视觉长上下文
图像理解, multimodal chat1000-3000ms目录平台整理
SpaceXAI: Grok 4.3x-ai/grok-4.3X Ai$0.181 / 1M tokens$0.362 / 1M tokens1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
SpaceXAI: Grok Build 0.1x-ai/grok-build-0.1OpenRouter$0.188 / 1M tokens$0.376 / 1M tokens256k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Xiaomi: MiMo-V2.5xiaomi/mimo-v2.5OpenRouter$0.027 / 1M tokens$0.054 / 1M tokens1.1M
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Xiaomi: MiMo-V2.5-Proxiaomi/mimo-v2.5-proOpenRouter$0.082 / 1M tokens$0.165 / 1M tokens1.1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Z.ai: GLM 4.5z-ai/glm-4.5OpenRouter$0.114 / 1M tokens$0.414 / 1M tokens131.1k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Z.ai: GLM 4.5 Airz-ai/glm-4.5-airOpenRouter$0.025 / 1M tokens$0.161 / 1M tokens131.1k
流式输出工具调用长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Z.ai: GLM 4.5Vz-ai/glm-4.5vOpenRouter$0.114 / 1M tokens$0.34 / 1M tokens65.5k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Z.ai: GLM 4.6z-ai/glm-4.6OpenRouter$0.081 / 1M tokens$0.328 / 1M tokens204.8k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Z.ai: GLM 4.6Vz-ai/glm-4.6vOpenRouter$0.058 / 1M tokens$0.169 / 1M tokens131.1k
流式输出工具调用JSON 模式视觉
图像理解, multimodal chat1000-3000ms目录平台整理
Z.ai: GLM 4.7z-ai/glm-4.7OpenRouter$0.075 / 1M tokens$0.33 / 1M tokens204.8k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Z.ai: GLM 4.7 Flashz-ai/glm-4.7-flashOpenRouter$0.012 / 1M tokens$0.075 / 1M tokens202.8k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Z.ai: GLM 5z-ai/glm-5OpenRouter$0.114 / 1M tokens$0.362 / 1M tokens204.8k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Z.ai: GLM 5 Turboz-ai/glm-5-turboOpenRouter$0.226 / 1M tokens$0.752 / 1M tokens202.8k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Z.ai: GLM 5.1z-ai/glm-5.1OpenRouter$0.185 / 1M tokens$0.58 / 1M tokens204.8k
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理
Z.ai: GLM 5.2z-ai/glm-5.2OpenRouter$0.226 / 1M tokens$0.773 / 1M tokens1M
流式输出工具调用JSON 模式长上下文
General chat via OpenRouter, API workloads1000-3000ms目录平台整理