Kimi K2 0905
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 billion active per forward pass. It supports long-context inference up to 256k tokens, extended from the previous 128k. This update improves agentic coding with higher accuracy and better generalization across scaffolds, and enhances frontend coding with more aesthetic and functional outputs for web, 3D, and related tasks. Kimi K2 is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. It excels across coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) benchmarks. The model is trained with a novel stack incorporating the MuonClip optimizer for stable large-scale MoE training.
moonshotai/kimi-k2-0905
- Context
- 262k tokens
- Completion cap
- 100,352
- Tools
- Yes
- JSON
- Yes
- Released
- 2025-09-04
Call it from Geek Hub
Same OpenAI SDK. Change the base URL and the model id.
curl https://api.geekhub.mx/v1/chat/completions \
-H "Authorization: Bearer $GEEKHUB_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "moonshotai/kimi-k2-0905",
"messages": [{"role": "user", "content": "Hola"}]
}'Get an API keyFrequently asked questions
- What is Kimi K2 0905?
- 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 billion active per forward pass. It supports long-context inference up to 256k tokens, extended from the previous 128k. This update improves agentic coding with higher accuracy and better generalization across scaffolds, and enhances frontend coding with more aesthetic and functional outputs for web, 3D, and related tasks. Kimi K2 is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. It excels across coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) benchmarks. The model is trained with a novel stack incorporating the MuonClip optimizer for stable large-scale MoE training. Kimi K2 0905 runs on the Geek Hub API (OpenAI-compatible). Model id: moonshotai/kimi-k2-0905.
- Is Kimi K2 0905 free?
- No. Input is $0.654 per 1M tokens and output is $2.7251 per 1M tokens on Geek Hub (markup included).
- What is the context length of Kimi K2 0905?
- Kimi K2 0905 has a 262k tokens context window. It supports up to 100,352 completion tokens.
- Does Kimi K2 0905 support tool calling and structured outputs?
- Kimi K2 0905 accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
- When was Kimi K2 0905 released?
- Kimi K2 0905 was released on 2025-09-04.
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