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.

ChatMoonshot262k tokens$0.654 / $2.7251 · 1M

moonshotai/kimi-k2-0905

Contexto
262k tokens
Máx. completion
100,352
Tools
Sí
JSON
Sí
Lanzamiento
2025-09-04

Llámalo desde Geek Hub

El mismo SDK de OpenAI. Cambia el base URL y el id del modelo.

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"}]
  }'
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Preguntas frecuentes

¿Qué es 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 corre en el API de Geek Hub (compatible con OpenAI). Id: moonshotai/kimi-k2-0905.
¿Kimi K2 0905 es gratis?
No. El input cuesta $0.654 / 1M tokens y el output $2.7251 / 1M tokens en Geek Hub (markup incluido).
¿Cuál es el contexto de Kimi K2 0905?
Kimi K2 0905 tiene una ventana de 262k tokens. Soporta hasta 100,352 tokens de completion.
¿Kimi K2 0905 soporta tool calling y structured outputs?
Kimi K2 0905 acepta tools y tool_choice para function calling. También soporta structured outputs con un JSON schema en response_format.
¿Cuándo se lanzó Kimi K2 0905?
Kimi K2 0905 se lanzó el 4 de septiembre de 2025.

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