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...
이 후보 목록은 어디에 쓰나?
Vision model APIs are useful for screenshots, receipts, product images, visual support tickets, and multimodal Q&A. The right choice depends on image input support, context size, price, and whether the same model must also produce structured JSON output. NextModel groups vision-capable candidates with price and capability labels so developers can test a small set of models quickly.
출처 기준: NextModel capability mapping and OpenRouter input-modality metadata when available.
Fit score
추천 후보 vision models
먼저 후보 목록으로 시작한 다음 실제 프롬프트로 테스트하고 운영 라우팅 전에 월간 비용을 비교합니다.
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...
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...
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...
비교표
가격, 공급자, 컨텍스트, 기능, 출처 기준으로 후보를 비교합니다.
운영 후보를 좁히거나 폴백 정책을 만들거나 모델 경제성을 비교할 때 사용합니다.
| Model | Provider | Input | Output | Context | Capabilities | Best for | Latency | Status | Source |
|---|---|---|---|---|---|---|---|---|---|
| Anthropic: Claude Opus 4.7anthropic/claude-opus-4.7 | Anthropic | $5 / 1M tokens | $25 / 1M tokens | 1M | Tool callingJSON modeLong contextReasoning | frontier reasoning, large codebase review | 2300-6800ms | Catalog | OpenRouter if available |
| Anthropic: Claude Sonnet 4.5anthropic/claude-sonnet-4.5 | Anthropic | $3 / 1M tokens | $15 / 1M tokens | 1M | Tool callingJSON modeLong contextReasoning | coding agents, code review | 1600-4800ms | Catalog | OpenRouter if available |
| Google: Gemini 2.5 Progoogle/gemini-2.5-pro | $1.25 / 1M tokens | $10 / 1M tokens | 1M | Tool callingVisionJSON modeLong context | long-context analysis, vision workflows | 1500-5000ms | Catalog | OpenRouter if available | |
| Google: Gemini 2.5 Flashgoogle/gemini-2.5-flash | $0.3 / 1M tokens | $2.50 / 1M tokens | 1M | Tool callingVisionJSON modeLong context | long-document summarization, image Q&A | 900-2800ms | Catalog | OpenRouter if available | |
| OpenAI: GPT-4o-miniopenai/gpt-4o-mini | OpenRouter | $0.15 / 1M tokens | $0.6 / 1M tokens | 128k | Tool callingVisionJSON modeLong context | low-cost chat, image understanding | 800-2400ms | Catalog | OpenRouter if available |
| MoonshotAI: Kimi K2.6moonshotai/kimi-k2.6 | Moonshot AI | $0.73 / 1M tokens | $3.49 / 1M tokens | 262.1k | JSON modeLong contextStreamingTool calling | long Chinese documents, contract review | 1400-4400ms | Catalog | OpenRouter if available |
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | Meta | $0.15 / 1M tokens | $0.6 / 1M tokens | 1M | JSON modeLong contextStreamingLow cost | open-model workflows, cost-sensitive long context | 950-2800ms | Catalog | OpenRouter if available |
| Mistral: Mistral Small 3.2 24Bmistralai/mistral-small-3.2-24b-instruct | Mistral AI | $0.1 / 1M tokens | $0.3 / 1M tokens | 128k | Tool callingJSON modeStreamingLow cost | translation, classification | 700-2300ms | Catalog | OpenRouter if available |
FAQ
Vision models FAQ
What should I compare before choosing a vision model API?
Compare input support, JSON output, latency, output-token cost, and the quality of answers on your own image samples.
Can low-cost models handle vision tasks?
Some low-cost models can handle lightweight vision tasks, but document-heavy or high-accuracy workflows should be benchmarked carefully.