GPT-5.1 Turbo vs o4 Pro: which model should you choose?
We compared GPT-5.1 Turbo and o4 Pro on price, context window and 12 benchmarks. o4 Pro has the stronger average benchmark score; o4 Pro is cheaper on a blended 3:1 basis.
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
o4 Pro
o4 Pro is a frontier model from OpenAI. It offers a 1,000,000-token context window, costs $19.37 per million input tokens and $70.19 per million output tokens, and averages 87.3 across the index's benchmark suite.
- Input
- $19.37 / 1M
- Output
- $70.19 / 1M
- Context
- 1,000,000
- Avg score
- 87.3
- Open weights
- No
Specification comparison
| Spec | GPT-5.1 Turbo | o4 Pro | Edge |
|---|---|---|---|
| Input price / 1M | $19.19 | $19.37 | A |
| Output price / 1M | $89.83 | $70.19 | B |
| Context window | 2,000,000 | 1,000,000 | A |
| Max output | 128,000 | 16,384 | A |
| Average score | 86.1 | 87.3 | B |
| Arena Elo | 1482.0 | 1471.2 | A |
| Open weights | No | No | Tie |
Benchmark comparison
GPT-5.1 Turbo wins 5, o4 Pro wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GPT-5.1 Turbo | o4 Pro | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 85.2 | 87.7 | 2.5 | o4 Pro |
| GPQA Diamond | 81.3 | 82.7 | 1.4 | o4 Pro |
| SWE-bench Verified | 74.7 | 78.5 | 3.8 | o4 Pro |
| HumanEval | 91.5 | 92.1 | 0.6 | o4 Pro |
| MATH-500 | 91.4 | 89.8 | 1.6 | GPT-5.1 Turbo |
| AIME 2025 | 84.7 | 89.9 | 5.2 | o4 Pro |
| LiveCodeBench | 84.6 | 81.8 | 2.8 | GPT-5.1 Turbo |
| IFEval | 93.4 | 90.9 | 2.5 | GPT-5.1 Turbo |
| TruthfulQA | 89.2 | 87.9 | 1.3 | GPT-5.1 Turbo |
| HellaSwag | 91.3 | 94.4 | 3.1 | o4 Pro |
| MMMU | 79.7 | 84.1 | 4.4 | o4 Pro |
| Arena Elo | 1482.0 | 1471.2 | 10.8 | GPT-5.1 Turbo |
Price analysis
On a blended 3:1 input-to-output basis, GPT-5.1 Turbo costs about $36.85 per million tokens and o4 Pro costs about $32.08. o4 Pro is roughly 13% 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 1,000,000 for o4 Pro. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, GPT-5.1 Turbo wins 5, o4 Pro wins 7, and 0 are tied. On the index average, o4 Pro leads GPT-5.1 Turbo by 1.2 points (87.3 versus 86.1).
The price picture favours o4 Pro. 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 o4 Pro for quality-sensitive work, and check whether its price holds at your expected volume before committing.
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.
Choose o4 Pro if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
FAQ
Is GPT-5.1 Turbo better than o4 Pro?
On the index average, o4 Pro leads GPT-5.1 Turbo by 1.2 points (87.3 versus 86.1). The better choice depends on price, context and your task. GPT-5.1 Turbo wins 5 benchmarks, o4 Pro wins 7.
Which is cheaper, GPT-5.1 Turbo or o4 Pro?
o4 Pro is cheaper on a blended 3:1 basis at about $32.08 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. o4 Pro has 1,000,000 tokens.
Are these models open weights?
GPT-5.1 Turbo is proprietary; o4 Pro is proprietary.
Which should I choose for production?
If you need a single default, start with o4 Pro for quality-sensitive work, and check whether its price holds at your expected volume before committing.