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Kimi K2.7 CodeOPEN
Kimi K2.7 Code (Moonshot AI): live API pricing, context window and the best open-source alternatives, tracked daily by OpenSourceAI.tech.
Prices update automatically — checked hourly against provider list prices.
Benchmarks & performance
Independent benchmark scores for Kimi K2.7 Code, measured by Artificial Analysis. Higher is better.
For the same budget, Kimi K2.7 Code delivers 4 times more capability. Open weights also mean you can self-host it and pay nothing per token.
About this model
Kimi K2.7 Code is an open-weight AI model by Moonshot AI. You can download and self-host it for free; the prices below are hosted-API list prices, tracked hourly, for when you prefer convenience over self-hosting.
Frequently asked questions
What is Kimi K2.7 Code?
Kimi K2.7 Code is an AI language model from Moonshot AI. It is open-weight: you can download it and run it on your own hardware, for free. It scores 41.9 on the Artificial Analysis intelligence index.
Is Kimi K2.7 Code free?
The weights are free and open — you can self-host Kimi K2.7 Code and pay nothing per token. If you prefer a hosted API, list prices are $0.73 per million input tokens and $3.5 per million output tokens.
What is Kimi K2.7 Code good at?
Independent benchmarks from Artificial Analysis give it GPQA 89.6%, Humanity's Last Exam 32.8%, Long Context Reasoning 66.3%, SciCode 47.5%, IFBench 63.1%, τ²-Bench 90.1%, τ-Bench Banking 18.1%, Terminal-Bench 67.4%, Terminal-Bench Hard 44.7%. It is particularly used for code generation.
How fast is Kimi K2.7 Code?
It generates about 36.2 tokens per second, with a median 1.34s delay before the first token. Measured independently by Artificial Analysis.
Can I self-host Kimi K2.7 Code?
Yes. Kimi K2.7 Code has open weights, so you can download it and run it on your own GPU or server with tools like Ollama, vLLM or llama.cpp — with no per-token cost.
Open-source alternatives
Depending on your workload, an open-weight model that you can self-host may cut costs dramatically or remove per-token pricing entirely. Our comparison pages put this model side by side with the strongest open-source contenders.