Claude 3.7 Sonnet Turbo vs Kimi K2: which model should you choose?
We compared Claude 3.7 Sonnet Turbo and Kimi K2 on price, context window and 12 benchmarks. Kimi K2 has the stronger average benchmark score; Kimi K2 is cheaper on a blended 3:1 basis.
Claude 3.7 Sonnet Turbo
Claude 3.7 Sonnet Turbo is a multimodal model from Anthropic. It offers a 200,000-token context window, costs $15.56 per million input tokens and $63.75 per million output tokens, and averages 82.3 across the index's benchmark suite.
- Input
- $15.56 / 1M
- Output
- $63.75 / 1M
- Context
- 200,000
- Avg score
- 82.3
- Open weights
- No
Kimi K2
Kimi K2 is a multimodal model from Moonshot AI. It offers a 128,000-token context window, costs $5.85 per million input tokens and $21.72 per million output tokens, and averages 83.0 across the index's benchmark suite.
- Input
- $5.85 / 1M
- Output
- $21.72 / 1M
- Context
- 128,000
- Avg score
- 83.0
- Open weights
- Yes
Specification comparison
| Spec | Claude 3.7 Sonnet Turbo | Kimi K2 | Edge |
|---|---|---|---|
| Input price / 1M | $15.56 | $5.85 | B |
| Output price / 1M | $63.75 | $21.72 | B |
| Context window | 200,000 | 128,000 | A |
| Max output | 16,384 | 65,536 | B |
| Average score | 82.3 | 83.0 | B |
| Arena Elo | 1458.8 | 1458.5 | A |
| Open weights | No | Yes | B |
Benchmark comparison
Claude 3.7 Sonnet Turbo wins 6, Kimi K2 wins 6, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Claude 3.7 Sonnet Turbo | Kimi K2 | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 82.1 | 83.3 | 1.2 | Kimi K2 |
| GPQA Diamond | 79.7 | 77.5 | 2.2 | Claude 3.7 Sonnet Turbo |
| SWE-bench Verified | 73.9 | 70.2 | 3.7 | Claude 3.7 Sonnet Turbo |
| HumanEval | 87.6 | 87.1 | 0.5 | Claude 3.7 Sonnet Turbo |
| MATH-500 | 86.8 | 85.3 | 1.5 | Claude 3.7 Sonnet Turbo |
| AIME 2025 | 81.4 | 85.1 | 3.7 | Kimi K2 |
| LiveCodeBench | 75.5 | 78.5 | 3.0 | Kimi K2 |
| IFEval | 87.4 | 91.5 | 4.1 | Kimi K2 |
| TruthfulQA | 82.6 | 84.8 | 2.2 | Kimi K2 |
| HellaSwag | 91.0 | 92.3 | 1.3 | Kimi K2 |
| MMMU | 77.6 | 77.5 | 0.1 | Claude 3.7 Sonnet Turbo |
| Arena Elo | 1458.8 | 1458.5 | 0.3 | Claude 3.7 Sonnet Turbo |
Price analysis
On a blended 3:1 input-to-output basis, Claude 3.7 Sonnet Turbo costs about $27.61 per million tokens and Kimi K2 costs about $9.82. Kimi K2 is roughly 64% cheaper than Claude 3.7 Sonnet Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Claude 3.7 Sonnet Turbo has the larger context window at 200,000 tokens, compared with 128,000 for Kimi K2. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Claude 3.7 Sonnet Turbo wins 6, Kimi K2 wins 6, and 0 are tied. On the index average, Kimi K2 leads Claude 3.7 Sonnet Turbo by 0.7 points (83.0 versus 82.3).
The price picture favours Kimi K2. The context picture favours Claude 3.7 Sonnet Turbo. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.
If you need a single default, start with Kimi K2 for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose Claude 3.7 Sonnet Turbo if
- You need the larger 200,000-token context window.
Choose Kimi K2 if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
- You need the larger 65,536-token output limit.
- You need open weights for self-hosting or fine-tuning.
FAQ
Is Claude 3.7 Sonnet Turbo better than Kimi K2?
On the index average, Kimi K2 leads Claude 3.7 Sonnet Turbo by 0.7 points (83.0 versus 82.3). The better choice depends on price, context and your task. Claude 3.7 Sonnet Turbo wins 6 benchmarks, Kimi K2 wins 6.
Which is cheaper, Claude 3.7 Sonnet Turbo or Kimi K2?
Kimi K2 is cheaper on a blended 3:1 basis at about $9.82 per million tokens, versus $27.61 for Claude 3.7 Sonnet Turbo.
Which has the larger context window?
Claude 3.7 Sonnet Turbo has the larger context window at 200,000 tokens. Kimi K2 has 128,000 tokens.
Are these models open weights?
Claude 3.7 Sonnet Turbo is proprietary; Kimi K2 is open weights.
Which should I choose for production?
If you need a single default, start with Kimi K2 for quality-sensitive work, and check whether its price holds at your expected volume before committing.