Head-to-head · frontier vs multimodal

Claude 3.7 Sonnet Pro vs Kimi K2 Instruct: which model should you choose?

We compared Claude 3.7 Sonnet Pro and Kimi K2 Instruct on price, context window and 12 benchmarks. Claude 3.7 Sonnet Pro has the stronger average benchmark score; Kimi K2 Instruct is cheaper on a blended 3:1 basis.

Anthropic

Claude 3.7 Sonnet Pro

Claude 3.7 Sonnet Pro is a frontier model from Anthropic. It offers a 128,000-token context window, costs $16.07 per million input tokens and $85.28 per million output tokens, and averages 83.3 across the index's benchmark suite.

Input
$16.07 / 1M
Output
$85.28 / 1M
Context
128,000
Avg score
83.3
Open weights
No
Full Claude 3.7 Sonnet Pro page
Moonshot AI

Kimi K2 Instruct

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.

Input
$5.80 / 1M
Output
$23.99 / 1M
Context
1,000,000
Avg score
82.3
Open weights
Yes
Full Kimi K2 Instruct page

Specification comparison

SpecClaude 3.7 Sonnet ProKimi K2 InstructEdge
Input price / 1M$16.07$5.80B
Output price / 1M$85.28$23.99B
Context window128,0001,000,000B
Max output8,19265,536B
Average score83.382.3A
Arena Elo1446.81458.6B
Open weightsNoYesB

Benchmark comparison

Claude 3.7 Sonnet Pro wins 7, Kimi K2 Instruct wins 4, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkClaude 3.7 Sonnet ProKimi K2 InstructGapWinner
MMLU-Pro85.786.50.8Kimi K2 Instruct
GPQA Diamond80.678.42.2Claude 3.7 Sonnet Pro
SWE-bench Verified71.475.13.7Kimi K2 Instruct
HumanEval90.087.32.7Claude 3.7 Sonnet Pro
MATH-50089.288.01.2Claude 3.7 Sonnet Pro
AIME 202581.577.34.2Claude 3.7 Sonnet Pro
LiveCodeBench74.174.10.0Tie
IFEval88.587.51.0Claude 3.7 Sonnet Pro
TruthfulQA86.082.83.2Claude 3.7 Sonnet Pro
HellaSwag89.790.20.5Kimi K2 Instruct
MMMU79.778.31.4Claude 3.7 Sonnet Pro
Arena Elo1446.81458.611.8Kimi K2 Instruct

Price analysis

On a blended 3:1 input-to-output basis, Claude 3.7 Sonnet Pro costs about $33.37 per million tokens and Kimi K2 Instruct costs about $10.35. Kimi K2 Instruct is roughly 69% cheaper than Claude 3.7 Sonnet Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.

Kimi K2 Instruct has the larger context window at 1,000,000 tokens, compared with 128,000 for Claude 3.7 Sonnet Pro. That matters for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, Claude 3.7 Sonnet Pro wins 7, Kimi K2 Instruct wins 4, and 1 are tied. On the index average, Claude 3.7 Sonnet Pro leads Kimi K2 Instruct by 1.0 points (83.3 versus 82.3).

The price picture favours Kimi K2 Instruct. The context picture favours Kimi K2 Instruct. 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 Claude 3.7 Sonnet Pro for quality-sensitive work and Kimi K2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

Choose Claude 3.7 Sonnet Pro if

  • You want the higher average benchmark score in this index.

Choose Kimi K2 Instruct if

  • Unit cost matters and you want the cheaper blended price.
  • You need the larger 1,000,000-token context window.
  • 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 Pro better than Kimi K2 Instruct?

On the index average, Claude 3.7 Sonnet Pro leads Kimi K2 Instruct by 1.0 points (83.3 versus 82.3). The better choice depends on price, context and your task. Claude 3.7 Sonnet Pro wins 7 benchmarks, Kimi K2 Instruct wins 4.

Which is cheaper, Claude 3.7 Sonnet Pro or Kimi K2 Instruct?

Kimi K2 Instruct is cheaper on a blended 3:1 basis at about $10.35 per million tokens, versus $33.37 for Claude 3.7 Sonnet Pro.

Which has the larger context window?

Kimi K2 Instruct has the larger context window at 1,000,000 tokens. Claude 3.7 Sonnet Pro has 128,000 tokens.

Are these models open weights?

Claude 3.7 Sonnet Pro is proprietary; Kimi K2 Instruct is open weights.

Which should I choose for production?

If you need a single default, start with Claude 3.7 Sonnet Pro for quality-sensitive work and Kimi K2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

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