Claude Haiku 4.5 Turbo vs Kimi K1.5 Instruct: which model should you choose?
We compared Claude Haiku 4.5 Turbo and Kimi K1.5 Instruct on price, context window and 12 benchmarks. Kimi K1.5 Instruct has the stronger average benchmark score; Kimi K1.5 Instruct is cheaper on a blended 3:1 basis.
Claude Haiku 4.5 Turbo
Claude Haiku 4.5 Turbo is a multimodal model from Anthropic. It offers a 200,000-token context window, costs $14.37 per million input tokens and $54.76 per million output tokens, and averages 80.0 across the index's benchmark suite.
- Input
- $14.37 / 1M
- Output
- $54.76 / 1M
- Context
- 200,000
- Avg score
- 80.0
- Open weights
- No
Kimi K1.5 Instruct
Kimi K1.5 Instruct is a multimodal model from Moonshot AI. It offers a 200,000-token context window, costs $5.15 per million input tokens and $28.20 per million output tokens, and averages 80.5 across the index's benchmark suite.
- Input
- $5.15 / 1M
- Output
- $28.20 / 1M
- Context
- 200,000
- Avg score
- 80.5
- Open weights
- Yes
Specification comparison
| Spec | Claude Haiku 4.5 Turbo | Kimi K1.5 Instruct | Edge |
|---|---|---|---|
| Input price / 1M | $14.37 | $5.15 | B |
| Output price / 1M | $54.76 | $28.20 | B |
| Context window | 200,000 | 200,000 | Tie |
| Max output | 32,768 | 4,096 | A |
| Average score | 80.0 | 80.5 | B |
| Arena Elo | 1434.5 | 1431.8 | A |
| Open weights | No | Yes | B |
Benchmark comparison
Claude Haiku 4.5 Turbo wins 6, Kimi K1.5 Instruct wins 6, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Claude Haiku 4.5 Turbo | Kimi K1.5 Instruct | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 80.6 | 83.0 | 2.4 | Kimi K1.5 Instruct |
| GPQA Diamond | 75.1 | 77.4 | 2.3 | Kimi K1.5 Instruct |
| SWE-bench Verified | 68.4 | 67.8 | 0.6 | Claude Haiku 4.5 Turbo |
| HumanEval | 87.0 | 84.0 | 3.0 | Claude Haiku 4.5 Turbo |
| MATH-500 | 83.7 | 82.6 | 1.1 | Claude Haiku 4.5 Turbo |
| AIME 2025 | 79.2 | 80.4 | 1.2 | Kimi K1.5 Instruct |
| LiveCodeBench | 71.7 | 71.1 | 0.6 | Claude Haiku 4.5 Turbo |
| IFEval | 87.1 | 86.2 | 0.9 | Claude Haiku 4.5 Turbo |
| TruthfulQA | 81.0 | 84.3 | 3.3 | Kimi K1.5 Instruct |
| HellaSwag | 88.1 | 90.2 | 2.1 | Kimi K1.5 Instruct |
| MMMU | 77.7 | 78.6 | 0.9 | Kimi K1.5 Instruct |
| Arena Elo | 1434.5 | 1431.8 | 2.7 | Claude Haiku 4.5 Turbo |
Price analysis
On a blended 3:1 input-to-output basis, Claude Haiku 4.5 Turbo costs about $24.47 per million tokens and Kimi K1.5 Instruct costs about $10.91. Kimi K1.5 Instruct is roughly 55% cheaper than Claude Haiku 4.5 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 200,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Claude Haiku 4.5 Turbo wins 6, Kimi K1.5 Instruct wins 6, and 0 are tied. On the index average, Kimi K1.5 Instruct leads Claude Haiku 4.5 Turbo by 0.5 points (80.5 versus 80.0).
The price picture favours Kimi K1.5 Instruct. The context picture is effectively a tie. 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 K1.5 Instruct for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose Claude Haiku 4.5 Turbo if
- You need the larger 32,768-token output limit.
Choose Kimi K1.5 Instruct if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
- You need open weights for self-hosting or fine-tuning.
FAQ
Is Claude Haiku 4.5 Turbo better than Kimi K1.5 Instruct?
On the index average, Kimi K1.5 Instruct leads Claude Haiku 4.5 Turbo by 0.5 points (80.5 versus 80.0). The better choice depends on price, context and your task. Claude Haiku 4.5 Turbo wins 6 benchmarks, Kimi K1.5 Instruct wins 6.
Which is cheaper, Claude Haiku 4.5 Turbo or Kimi K1.5 Instruct?
Kimi K1.5 Instruct is cheaper on a blended 3:1 basis at about $10.91 per million tokens, versus $24.47 for Claude Haiku 4.5 Turbo.
Which has the larger context window?
Both models list a 200,000-token context window.
Are these models open weights?
Claude Haiku 4.5 Turbo is proprietary; Kimi K1.5 Instruct is open weights.
Which should I choose for production?
If you need a single default, start with Kimi K1.5 Instruct for quality-sensitive work, and check whether its price holds at your expected volume before committing.