Head-to-head · frontier vs frontier

GPT-5.1 Pro vs GPT-5.2 Turbo: which model should you choose?

We compared GPT-5.1 Pro and GPT-5.2 Turbo on price, context window and 12 benchmarks. GPT-5.1 Pro has the stronger average benchmark score; GPT-5.2 Turbo is cheaper on a blended 3:1 basis.

OpenAI

GPT-5.1 Pro

GPT-5.1 Pro is a frontier model from OpenAI. It offers a 200,000-token context window, costs $19.77 per million input tokens and $100.32 per million output tokens, and averages 87.8 across the index's benchmark suite.

Input
$19.77 / 1M
Output
$100.32 / 1M
Context
200,000
Avg score
87.8
Open weights
No
Full GPT-5.1 Pro page
OpenAI

GPT-5.2 Turbo

GPT-5.2 Turbo is a frontier model from OpenAI. It offers a 1,000,000-token context window, costs $20.73 per million input tokens and $96.05 per million output tokens, and averages 87.4 across the index's benchmark suite.

Input
$20.73 / 1M
Output
$96.05 / 1M
Context
1,000,000
Avg score
87.4
Open weights
No
Full GPT-5.2 Turbo page

Specification comparison

SpecGPT-5.1 ProGPT-5.2 TurboEdge
Input price / 1M$19.77$20.73A
Output price / 1M$100.32$96.05B
Context window200,0001,000,000B
Max output32,7688,192A
Average score87.887.4A
Arena Elo1490.01500.3B
Open weightsNoNoTie

Benchmark comparison

GPT-5.1 Pro wins 4, GPT-5.2 Turbo wins 8, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkGPT-5.1 ProGPT-5.2 TurboGapWinner
MMLU-Pro86.287.31.1GPT-5.2 Turbo
GPQA Diamond83.484.00.6GPT-5.2 Turbo
SWE-bench Verified80.177.42.7GPT-5.1 Pro
HumanEval91.193.22.1GPT-5.2 Turbo
MATH-50095.192.72.4GPT-5.1 Pro
AIME 202590.686.73.9GPT-5.1 Pro
LiveCodeBench82.282.50.3GPT-5.2 Turbo
IFEval94.892.02.8GPT-5.1 Pro
TruthfulQA86.987.30.4GPT-5.2 Turbo
HellaSwag93.895.51.7GPT-5.2 Turbo
MMMU81.683.31.7GPT-5.2 Turbo
Arena Elo1490.01500.310.3GPT-5.2 Turbo

Price analysis

On a blended 3:1 input-to-output basis, GPT-5.1 Pro costs about $39.91 per million tokens and GPT-5.2 Turbo costs about $39.56. GPT-5.2 Turbo is roughly 1% cheaper than GPT-5.1 Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.

GPT-5.2 Turbo has the larger context window at 1,000,000 tokens, compared with 200,000 for GPT-5.1 Pro. That matters for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, GPT-5.1 Pro wins 4, GPT-5.2 Turbo wins 8, and 0 are tied. On the index average, GPT-5.1 Pro leads GPT-5.2 Turbo by 0.4 points (87.8 versus 87.4).

The price picture favours GPT-5.2 Turbo. The context picture favours GPT-5.2 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 GPT-5.1 Pro for quality-sensitive work and GPT-5.2 Turbo for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

Choose GPT-5.1 Pro if

  • You want the higher average benchmark score in this index.
  • You need the larger 32,768-token output limit.

Choose GPT-5.2 Turbo if

  • Unit cost matters and you want the cheaper blended price.
  • You need the larger 1,000,000-token context window.

FAQ

Is GPT-5.1 Pro better than GPT-5.2 Turbo?

On the index average, GPT-5.1 Pro leads GPT-5.2 Turbo by 0.4 points (87.8 versus 87.4). The better choice depends on price, context and your task. GPT-5.1 Pro wins 4 benchmarks, GPT-5.2 Turbo wins 8.

Which is cheaper, GPT-5.1 Pro or GPT-5.2 Turbo?

GPT-5.2 Turbo is cheaper on a blended 3:1 basis at about $39.56 per million tokens, versus $39.91 for GPT-5.1 Pro.

Which has the larger context window?

GPT-5.2 Turbo has the larger context window at 1,000,000 tokens. GPT-5.1 Pro has 200,000 tokens.

Are these models open weights?

GPT-5.1 Pro is proprietary; GPT-5.2 Turbo is proprietary.

Which should I choose for production?

If you need a single default, start with GPT-5.1 Pro for quality-sensitive work and GPT-5.2 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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