MoonshotAI: Kimi K2 Thinking
moonshotai/kimi-k2-thinking- Context window
- 262,144 tokens
- Maximum output
- 235,929 tokens
- Input price
- $0.6 per 1M tokens
- Output price
- $2.5 per 1M tokens
- Modalities
- text
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Official description
Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-of-Experts (MoE) architecture introduced in...
Read the official model reference ↗.
Where this model fits
moonshotai/kimi-k2-thinking is part of the OpenRouter API catalog. Its documented modalities are text. Choose it against the request format, output requirements and operational limits of your application.
The source metadata identifies support for router hosting. Confirm endpoint-specific parameters in the official reference before integrating that capability.
For a repeatable evaluation, use representative requests, inspect structured output or tool calls, and log latency and usage in your own account. Catalog metadata establishes compatibility; it does not measure answer quality on your workload. Start from the provider guide for authentication and endpoint setup.
Current pricing
| Model | Price type | USD | Unit | Tier | Region | Source |
|---|---|---|---|---|---|---|
| MoonshotAI: Kimi K2 Thinking | Input | $0.6 | per 1M tokens | Standard | See source | Official source ↗ |
| MoonshotAI: Kimi K2 Thinking | Output | $2.5 | per 1M tokens | Standard | See source | Official source ↗ |
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Estimate request, daily and monthly usage in the API cost calculator.
Rate limits and availability
Published limits have not yet been verified for this selection. Check the official limits documentation and your account console.
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Account-specific capacity may differ. Check the provider rate-limit guide and the free-tier conditions.
Three alternatives to compare
These alternatives share a documented modality and have the closest combination of input price and context size in the current catalog. This is a specification comparison, not a quality benchmark.
| Model | Provider | Input / 1M tokens | Context |
|---|---|---|---|
| MoonshotAI: Kimi K2 0905 | OpenRouter | $0.6 | 262,144 |
| NVIDIA: Nemotron 3 Ultra | OpenRouter | $0.625 | 262,144 |
| Qwen: Qwen3.5 397B A17B | OpenRouter | $0.55 | 262,144 |
Use the exact identifier in Python
This identifier fragment belongs in the authenticated request described in the provider Python tutorial. The tutorial covers the correct SDK, endpoint, environment variable and response shape.
model = "moonshotai\/kimi-k2-thinking"
# Pass model to the provider-specific request in the tutorial.Recent changes
- OpenRouter · MoonshotAI: Kimi K2 Thinking — Amount UsdNot previously recorded → Price category: output · USD: 2.5 · Unit: per 1M tokensSource ↗
- OpenRouter · MoonshotAI: Kimi K2 Thinking — Amount UsdNot previously recorded → Price category: input · USD: 0.6 · Unit: per 1M tokensSource ↗
- OpenRouter · MoonshotAI: Kimi K2 Thinking — First SeenNot previously recorded → Model: MoonshotAI: Kimi K2 ThinkingSource ↗
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Frequently asked questions
What is the exact API model identifier?
moonshotai/kimi-k2-thinking exactly as shown in the provider model reference. Display names are not interchangeable with API identifiers.How much does this model cost?
How much input can the model accept?
Can I use a free tier?
Where do these model facts come from?
Sources
Last verified · Source ↗