Head-to-head · frontier vs frontier

Claude Opus 4.5 vs GPT-5.1 Turbo: which model should you choose?

We compared Claude Opus 4.5 and GPT-5.1 Turbo on price, context window and 12 benchmarks. Claude Opus 4.5 has the stronger average benchmark score; Claude Opus 4.5 is cheaper on a blended 3:1 basis.

Anthropic

Claude Opus 4.5

Claude Opus 4.5 is a frontier model from Anthropic. It offers a 400,000-token context window, costs $19.42 per million input tokens and $75.27 per million output tokens, and averages 87.7 across the index's benchmark suite.

Input
$19.42 / 1M
Output
$75.27 / 1M
Context
400,000
Avg score
87.7
Open weights
No
Full Claude Opus 4.5 page
OpenAI

GPT-5.1 Turbo

GPT-5.1 Turbo is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $19.19 per million input tokens and $89.83 per million output tokens, and averages 86.1 across the index's benchmark suite.

Input
$19.19 / 1M
Output
$89.83 / 1M
Context
2,000,000
Avg score
86.1
Open weights
No
Full GPT-5.1 Turbo page

Specification comparison

SpecClaude Opus 4.5GPT-5.1 TurboEdge
Input price / 1M$19.42$19.19B
Output price / 1M$75.27$89.83A
Context window400,0002,000,000B
Max output4,096128,000B
Average score87.786.1A
Arena Elo1491.21482.0A
Open weightsNoNoTie

Benchmark comparison

Claude Opus 4.5 wins 10, GPT-5.1 Turbo wins 2, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkClaude Opus 4.5GPT-5.1 TurboGapWinner
MMLU-Pro87.085.21.8Claude Opus 4.5
GPQA Diamond81.781.30.4Claude Opus 4.5
SWE-bench Verified77.174.72.4Claude Opus 4.5
HumanEval93.791.52.2Claude Opus 4.5
MATH-50093.791.42.3Claude Opus 4.5
AIME 202589.884.75.1Claude Opus 4.5
LiveCodeBench85.084.60.4Claude Opus 4.5
IFEval92.593.40.9GPT-5.1 Turbo
TruthfulQA88.189.21.1GPT-5.1 Turbo
HellaSwag92.491.31.1Claude Opus 4.5
MMMU84.279.74.5Claude Opus 4.5
Arena Elo1491.21482.09.2Claude Opus 4.5

Price analysis

On a blended 3:1 input-to-output basis, Claude Opus 4.5 costs about $33.38 per million tokens and GPT-5.1 Turbo costs about $36.85. Claude Opus 4.5 is roughly 9% cheaper than GPT-5.1 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.

GPT-5.1 Turbo has the larger context window at 2,000,000 tokens, compared with 400,000 for Claude Opus 4.5. That matters for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, Claude Opus 4.5 wins 10, GPT-5.1 Turbo wins 2, and 0 are tied. On the index average, Claude Opus 4.5 leads GPT-5.1 Turbo by 1.6 points (87.7 versus 86.1).

The price picture favours Claude Opus 4.5. The context picture favours GPT-5.1 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 Claude Opus 4.5 for quality-sensitive work, and check whether its price holds at your expected volume before committing.

Choose Claude Opus 4.5 if

  • You want the higher average benchmark score in this index.
  • Unit cost matters and you want the cheaper blended price.

Choose GPT-5.1 Turbo if

  • You need the larger 2,000,000-token context window.
  • You need the larger 128,000-token output limit.

FAQ

Is Claude Opus 4.5 better than GPT-5.1 Turbo?

On the index average, Claude Opus 4.5 leads GPT-5.1 Turbo by 1.6 points (87.7 versus 86.1). The better choice depends on price, context and your task. Claude Opus 4.5 wins 10 benchmarks, GPT-5.1 Turbo wins 2.

Which is cheaper, Claude Opus 4.5 or GPT-5.1 Turbo?

Claude Opus 4.5 is cheaper on a blended 3:1 basis at about $33.38 per million tokens, versus $36.85 for GPT-5.1 Turbo.

Which has the larger context window?

GPT-5.1 Turbo has the larger context window at 2,000,000 tokens. Claude Opus 4.5 has 400,000 tokens.

Are these models open weights?

Claude Opus 4.5 is proprietary; GPT-5.1 Turbo is proprietary.

Which should I choose for production?

If you need a single default, start with Claude Opus 4.5 for quality-sensitive work, and check whether its price holds at your expected volume before committing.

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