Kimi K2 Instruct: pricing, context window and benchmarks
Kimi K2 Instruct is a multimodal model from Moonshot AI. It offers a 1,000,000-token context window, costs $5.80 per million input tokens and $23.99 per million output tokens, and averages 82.3 across the index's benchmark suite.
Pricing
Kimi K2 Instruct costs $5.80 per million input tokens and $23.99 per million output tokens. A blended 3:1 input-to-output mix works out to about $10.35 per million tokens. Cached input is listed at $0.85 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $5.80 | per 1M tokens |
| Output | $23.99 | per 1M tokens |
| Cached input | $0.85 | per 1M tokens |
| Blended 3:1 | $10.35 | estimate per 1M tokens |
| 1M in + 1M out | $29.79 | estimate |
Benchmarks
Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 86.5 | 44 | 93th | |
| GPQA Diamond | 78.4 | 76 | 87th | |
| SWE-bench Verified | 75.1 | 40 | 93th | |
| HumanEval | 87.3 | 82 | 86th | |
| MATH-500 | 88.0 | 67 | 89th | |
| AIME 2025 | 77.3 | 124 | 79th | |
| LiveCodeBench | 74.1 | 108 | 82th | |
| IFEval | 87.5 | 116 | 81th | |
| TruthfulQA | 82.8 | 112 | 81th | |
| HellaSwag | 90.2 | 83 | 86th | |
| MMMU | 78.3 | 88 | 85th | |
| Arena Elo | 1458.6 | 55 | 91th |
What Kimi K2 Instruct is good for
Kimi K2 Instruct is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $5.80 per million input tokens, it sits in the mid-range of the index, and the 1,000,000-token context window is enough for large files and multi-file diffs.
Strengths
- Large 1,000,000-token context window for long documents and agent traces.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
- Accepts more than text, including image input where the provider supports it.
- Reasoning-oriented profile, useful for multi-step problems and structured analysis.
- Coding benchmarks are a relative strength within its tier.
Trade-offs
- No standout weakness in the indexed specifications, but real-world behaviour still needs testing.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| DeepSeek-V3.2 Chat | DeepSeek | 1000000 | $5.80 | 82.5 |
| DeepSeek-R1 Chat | DeepSeek | 400000 | $5.62 | 82.4 |
| GPT-4.1 | OpenAI | 1000000 | $15.71 | 82.4 |
| Claude 3.7 Sonnet Turbo | Anthropic | 200000 | $15.56 | 82.3 |
| Kimi K2 Instruct | Moonshot AI | 1000000 | $5.80 | 82.3 |
| Kimi K2 Chat | Moonshot AI | 400000 | $5.74 | 82.1 |
FAQ
How much does Kimi K2 Instruct cost?
Kimi K2 Instruct is listed at $5.80 per million input tokens and $23.99 per million output tokens. Cached input is $0.85 per million tokens. A blended 3:1 input-to-output mix is about $10.35 per million tokens.
What is the context window of Kimi K2 Instruct?
Kimi K2 Instruct has a context window of 1,000,000 tokens and can emit up to 65,536 output tokens per request in this index.
Is Kimi K2 Instruct open weights?
Yes. Kimi K2 Instruct is listed as an open-weight model under a open weights licence.
How does Kimi K2 Instruct score on benchmarks?
Kimi K2 Instruct averages 82.3 across the scored benchmarks in this index, ranking #83 of 600 models. Its strongest relative result is Arena Elo at 1458.6.
What is Kimi K2 Instruct best for?
Kimi K2 Instruct is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $5.80 per million input tokens, it sits in the mid-range of the index, and the 1,000,000-token context window is enough for large files and multi-file diffs.