Head-to-head · multimodal vs multimodal

Claude Haiku 4.5 Turbo vs Kimi K1.5: which model should you choose?

We compared Claude Haiku 4.5 Turbo and Kimi K1.5 on price, context window and 12 benchmarks. Kimi K1.5 has the stronger average benchmark score; Kimi K1.5 is cheaper on a blended 3:1 basis.

Anthropic

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
Full Claude Haiku 4.5 Turbo page
Moonshot AI

Kimi K1.5

Kimi K1.5 is a multimodal model from Moonshot AI. It offers a 128,000-token context window, costs $5.19 per million input tokens and $21.20 per million output tokens, and averages 80.7 across the index's benchmark suite.

Input
$5.19 / 1M
Output
$21.20 / 1M
Context
128,000
Avg score
80.7
Open weights
Yes
Full Kimi K1.5 page

Specification comparison

SpecClaude Haiku 4.5 TurboKimi K1.5Edge
Input price / 1M$14.37$5.19B
Output price / 1M$54.76$21.20B
Context window200,000128,000A
Max output32,7684,096A
Average score80.080.7B
Arena Elo1434.51432.2A
Open weightsNoYesB

Benchmark comparison

Claude Haiku 4.5 Turbo wins 5, Kimi K1.5 wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkClaude Haiku 4.5 TurboKimi K1.5GapWinner
MMLU-Pro80.682.72.1Kimi K1.5
GPQA Diamond75.174.40.7Claude Haiku 4.5 Turbo
SWE-bench Verified68.468.20.2Claude Haiku 4.5 Turbo
HumanEval87.087.10.1Kimi K1.5
MATH-50083.785.31.6Kimi K1.5
AIME 202579.280.81.6Kimi K1.5
LiveCodeBench71.771.10.6Claude Haiku 4.5 Turbo
IFEval87.187.90.8Kimi K1.5
TruthfulQA81.084.73.7Kimi K1.5
HellaSwag88.187.20.9Claude Haiku 4.5 Turbo
MMMU77.777.80.1Kimi K1.5
Arena Elo1434.51432.22.3Claude 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 costs about $9.19. Kimi K1.5 is roughly 62% 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.

Claude Haiku 4.5 Turbo has the larger context window at 200,000 tokens, compared with 128,000 for Kimi K1.5. That matters for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, Claude Haiku 4.5 Turbo wins 5, Kimi K1.5 wins 7, and 0 are tied. On the index average, Kimi K1.5 leads Claude Haiku 4.5 Turbo by 0.7 points (80.7 versus 80.0).

The price picture favours Kimi K1.5. The context picture favours Claude Haiku 4.5 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 K1.5 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 200,000-token context window.
  • You need the larger 32,768-token output limit.

Choose Kimi K1.5 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?

On the index average, Kimi K1.5 leads Claude Haiku 4.5 Turbo by 0.7 points (80.7 versus 80.0). The better choice depends on price, context and your task. Claude Haiku 4.5 Turbo wins 5 benchmarks, Kimi K1.5 wins 7.

Which is cheaper, Claude Haiku 4.5 Turbo or Kimi K1.5?

Kimi K1.5 is cheaper on a blended 3:1 basis at about $9.19 per million tokens, versus $24.47 for Claude Haiku 4.5 Turbo.

Which has the larger context window?

Claude Haiku 4.5 Turbo has the larger context window at 200,000 tokens. Kimi K1.5 has 128,000 tokens.

Are these models open weights?

Claude Haiku 4.5 Turbo is proprietary; Kimi K1.5 is open weights.

Which should I choose for production?

If you need a single default, start with Kimi K1.5 for quality-sensitive work, and check whether its price holds at your expected volume before committing.

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