Head-to-head · frontier vs multimodal

Claude 3.7 Sonnet Pro vs Grok 3 Turbo: which model should you choose?

We compared Claude 3.7 Sonnet Pro and Grok 3 Turbo on price, context window and 12 benchmarks. Claude 3.7 Sonnet Pro has the stronger average benchmark score; Grok 3 Turbo 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
xAI

Grok 3 Turbo

Grok 3 Turbo is a multimodal model from xAI. It offers a 128,000-token context window, costs $15.97 per million input tokens and $70.13 per million output tokens, and averages 83.1 across the index's benchmark suite.

Input
$15.97 / 1M
Output
$70.13 / 1M
Context
128,000
Avg score
83.1
Open weights
No
Full Grok 3 Turbo page

Specification comparison

SpecClaude 3.7 Sonnet ProGrok 3 TurboEdge
Input price / 1M$16.07$15.97B
Output price / 1M$85.28$70.13B
Context window128,000128,000Tie
Max output8,19265,536B
Average score83.383.1A
Arena Elo1446.81438.4A
Open weightsNoNoTie

Benchmark comparison

Claude 3.7 Sonnet Pro wins 5, Grok 3 Turbo wins 5, and 2 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkClaude 3.7 Sonnet ProGrok 3 TurboGapWinner
MMLU-Pro85.783.72.0Claude 3.7 Sonnet Pro
GPQA Diamond80.679.11.5Claude 3.7 Sonnet Pro
SWE-bench Verified71.471.40.0Tie
HumanEval90.086.83.2Claude 3.7 Sonnet Pro
MATH-50089.285.63.6Claude 3.7 Sonnet Pro
AIME 202581.583.11.6Grok 3 Turbo
LiveCodeBench74.176.42.3Grok 3 Turbo
IFEval88.590.72.2Grok 3 Turbo
TruthfulQA86.086.00.0Tie
HellaSwag89.790.20.5Grok 3 Turbo
MMMU79.781.31.6Grok 3 Turbo
Arena Elo1446.81438.48.4Claude 3.7 Sonnet Pro

Price analysis

On a blended 3:1 input-to-output basis, Claude 3.7 Sonnet Pro costs about $33.37 per million tokens and Grok 3 Turbo costs about $29.51. Grok 3 Turbo is roughly 12% 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.

Both models list a 128,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, Claude 3.7 Sonnet Pro wins 5, Grok 3 Turbo wins 5, and 2 are tied. On the index average, Claude 3.7 Sonnet Pro leads Grok 3 Turbo by 0.2 points (83.3 versus 83.1).

The price picture favours Grok 3 Turbo. 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 Claude 3.7 Sonnet Pro for quality-sensitive work and Grok 3 Turbo 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 Grok 3 Turbo if

  • Unit cost matters and you want the cheaper blended price.
  • You need the larger 65,536-token output limit.

FAQ

Is Claude 3.7 Sonnet Pro better than Grok 3 Turbo?

On the index average, Claude 3.7 Sonnet Pro leads Grok 3 Turbo by 0.2 points (83.3 versus 83.1). The better choice depends on price, context and your task. Claude 3.7 Sonnet Pro wins 5 benchmarks, Grok 3 Turbo wins 5.

Which is cheaper, Claude 3.7 Sonnet Pro or Grok 3 Turbo?

Grok 3 Turbo is cheaper on a blended 3:1 basis at about $29.51 per million tokens, versus $33.37 for Claude 3.7 Sonnet Pro.

Which has the larger context window?

Both models list a 128,000-token context window.

Are these models open weights?

Claude 3.7 Sonnet Pro is proprietary; Grok 3 Turbo is proprietary.

Which should I choose for production?

If you need a single default, start with Claude 3.7 Sonnet Pro for quality-sensitive work and Grok 3 Turbo for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

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