Senarai pendek model

API model pengekodan terbaik untuk ejen dan semakan kod

Bandingkan API model berfokus kod mengikut konteks, sokongan tool, output JSON, latensi, harga dan peranan produksi yang disyorkan.

Untuk apa senarai pendek ini?: Model pengekodan

Pemilihan model pengekodan bergantung pada saiz repositori, keperluan tool calling, kebolehpercayaan arahan dan kos output yang panjang. Pembantu yang membaca codebase besar memerlukan ekonomi yang berbeza daripada fungsi pelengkap kod yang ringkas. NextModel menonjolkan konteks, sokongan tool, harga dan panduan penggunaan supaya pasukan boleh memilih model utama serta dasar fallback.

Asas sumber: Taksonomi use case NextModel dan metadata parameter OpenRouter yang disokong apabila tersedia. · Dikemas kini 2026-07-01

Fit score

Calon disyorkan model pengekodan

Mulakan dengan senarai pendek, kemudian uji prompt sebenar dan bandingkan kos bulanan sebelum routing produksi.

DeepSeekCatalogHealthytypical

DeepSeek-V4-1-Flash-GLB via NextModel: 1M-token context; $0.3 / 1M tokens in / $1.20 / 1M tokens out per 1M tokens. Capabilities: streaming.

$0.3 / 1M tokensInput$1.20 / 1M tokensOutput1MContext
Best forChinese Q&A, general chat
Streaming
Platform curatedCurated and maintained in the NextModel catalog
View details
OpenAICatalog

Whisper Large V3 Turbo via NextModel: context unpublished; $0 / 1M tokens in / $0 / 1M tokens out per 1M tokens. Capabilities: streaming.

$0 / 1M tokensInput—Output—Context
Best forGeneral chat via OpenAI, API workloads
Streaming
Platform curatedCurated and maintained in the NextModel catalog
View details
GoogleCatalogHealthytypical

‌Gemini 4 Argon via NextModel: 1M-token context; $2 / 1M tokens in / $10 / 1M tokens out per 1M tokens. Capabilities: streaming, tool, json.

$2 / 1M tokensInput$10 / 1M tokensOutput1MContext
Best forimage understanding, multimodal chat
StreamingTool callingJSON modeVisionLong context
Platform curatedCurated and maintained in the NextModel catalog
View details
AnthropicCatalogHealthyfast

Claude Haiku 5.5 via NextModel: 1M-token context; Starting at $0.1 / 1M tokens in / $0.5 / 1M tokens out per 1M tokens. Capabilities: streaming, tool, json.

Starting at $0.1 / 1M tokensInput$0.5 / 1M tokensOutput1MContext
Best forimage understanding, multimodal chat
StreamingTool callingJSON modeVisionLong context
Platform curatedCurated and maintained in the NextModel catalog
View details

Jadual perbandingan

Bandingkan senarai pendek mengikut harga, penyedia, konteks, keupayaan dan sumber.

Gunakan paparan ini untuk mengecilkan senarai produksi, membina dasar fallback atau membandingkan ekonomi model.

ModelProviderInputOutputContextCapabilitiesBest forLatencyStatusSource
DeepSeek-V4-1-Flash-GLBdeepseek/deepseek-v4-1-flash-glbDeepSeek$0.3 / 1M tokens$1.20 / 1M tokens1M
Streaming
Chinese Q&A, general chat1557-3097msCatalogPlatform curated
Whisper Large V3 Turboopenai/whisper-large-v3-turboOpenAI$0 / 1M tokens$0 / 1M tokens—
Streaming
General chat via OpenAI, API workloads0-0msCatalogPlatform curated
‌Gemini 4 Argongoogle/gemini-4-argonGoogle$2 / 1M tokens$10 / 1M tokens1M
StreamingTool callingJSON modeVision
image understanding, multimodal chat2974-10589msCatalogPlatform curated
Claude Haiku 5.5anthropic/claude-haiku-5.5AnthropicStarting at $0.1 / 1M tokens$0.5 / 1M tokens1M
StreamingTool callingJSON modeVision
image understanding, multimodal chat1321-2017msCatalogPlatform curated
Doubao Seedance 2.5doubao/doubao-seedance-2-5-260628Doubao$0.225 / s——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated
Dreamina-Seedance 2.0 Fastdreamina/dreamina-seedance-2-0-fast-260128Dreamina$0.122 / s——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated
Dreamina Seedance 2.5dreamina/dreamina-seedance-2-5-260628Dreamina$0.234 / s——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated
Gemini 3 Pro Image (Nano Banana Pro) gemini/gemini-3-pro-imageGemini$0.314 / image——
StreamingVision
image understanding, multimodal chat0-0msCatalogPlatform curated

FAQ

Model pengekodan FAQ

Apa yang menjadikan model sesuai untuk ejen kod?

Konteks yang panjang, tool calling yang boleh dipercayai, output berstruktur dan pematuhan arahan yang stabil lebih penting daripada harga token semata-mata.

Bagaimana pasukan harus mengawal kos ejen kod?

Gunakan dasar bajet, bandingkan kos output yang panjang dan route tugas mudah ke model yang lebih murah sebelum menaikkan kes yang sukar.