Moonshot AI
RankedEnough results for an index.Kimi K2 Thinking
Kimi K2 Thinking is a model from Moonshot AI. 10 benchmarks count toward its index, in 4 categories.
IndexAll categories, out of 100.48.2±8.6Median 51.0
CoverageIndex weight that has results.65%
SpeedOutput tokens per second.48/sMedian 67/s
First tokenSeconds to the first output token.1.8 sMedian 1.3 s
Input / 1MUS dollars per 1M input tokens.$0.60Median $0.60
Output / 1MUS dollars per 1M output tokens.$2.50Median $2.55
ContextMaximum tokens in one request.262KMedian 262K
EloLMArena rating and rank.—Median 1422
Details
From OpenRouter- API IDThe model ID on OpenRouter.
moonshotai/kimi-k2-thinking- Max outputMaximum output tokens per request.
- 98K
- Knowledge cutoffLast date of training data.
- —
- ToolsTool calls on OpenRouter.
- Yes
- JSON outputOutput follows a given JSON schema.
- Yes
- Cache read / 1MUS dollars per 1M cached tokens.
- $0.15
- WeightsLink to the published weights.
- Hugging Face (opens in a new tab) ↗
- RetiresDate OpenRouter removes the model.
- —
Where to run
APIs that serve this model.ProviderTypeMaker, cloud, host or router.InputOutputContext
US dollars per 1M tokens, list price. From models.dev (opens in a new tab) (MIT).
Run locally
1026.41B parameters- 16-bit
- 2156.5 GB
- 8-bit
- 1146.1 GB
- 4-bit
- 654.4 GB
Memory need with a short context. The 4-bit copy needs more than 128 GB. Compare local models
Capabilities
Index per category, out of 100.Results
10 countedBenchmarkThe benchmark name.ResultThe score from the source.PlacePlace among results on this benchmark.
Sources
BenchLMCC BY-NC 4.0OpenRouterTerms restrict reuseVals AINo licence statedEpoch AICC BYSWE-bench teamNo licence statedmodels.devMITHistory
5 releases23 Oct 202612 Nov 2026
23 Oct 202612 Nov 2026
Questions
- How much does Kimi K2 Thinking cost?
- $0.60 per 1M input tokens, $2.50 per 1M output tokens.
- How good is Kimi K2 Thinking?
- Its index is 48.2 out of 100. That is place 159 of 283 ranked models.
- What is Kimi K2 Thinking best at?
- Math: 50.5 out of 100, place 85 of 168.
- How fast is Kimi K2 Thinking?
- 48 output tokens per second, 1.8 s to the first token.
- What is the context window of Kimi K2 Thinking?
- 262K tokens.
- Is Kimi K2 Thinking open source?
- Yes. Its weights are published.
- When was Kimi K2 Thinking released?
- November 2025.
Badge
- HTML
<a href="https://inference360.ai/models/moonshot-ai-kimi-k2-thinking"><img src="https://inference360.ai/badges/moonshot-ai-kimi-k2-thinking.svg" alt="Kimi K2 Thinking on Inference360: place 159 of 283, index 48.2" height="20"></a>- Markdown
[](https://inference360.ai/models/moonshot-ai-kimi-k2-thinking)