GPT-5.1 Pro vs o4 Max: which model should you choose?
We compared GPT-5.1 Pro and o4 Max on price, context window and 12 benchmarks. GPT-5.1 Pro has the stronger average benchmark score; o4 Max is cheaper on a blended 3:1 basis.
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
o4 Max
o4 Max is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $19.51 per million input tokens and $93.98 per million output tokens, and averages 86.2 across the index's benchmark suite.
- Input
- $19.51 / 1M
- Output
- $93.98 / 1M
- Context
- 2,000,000
- Avg score
- 86.2
- Open weights
- No
Specification comparison
| Spec | GPT-5.1 Pro | o4 Max | Edge |
|---|---|---|---|
| Input price / 1M | $19.77 | $19.51 | B |
| Output price / 1M | $100.32 | $93.98 | B |
| Context window | 200,000 | 2,000,000 | B |
| Max output | 32,768 | 65,536 | B |
| Average score | 87.8 | 86.2 | A |
| Arena Elo | 1490.0 | 1486.0 | A |
| Open weights | No | No | Tie |
Benchmark comparison
GPT-5.1 Pro wins 8, o4 Max wins 4, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GPT-5.1 Pro | o4 Max | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 86.2 | 86.3 | 0.1 | o4 Max |
| GPQA Diamond | 83.4 | 80.1 | 3.3 | GPT-5.1 Pro |
| SWE-bench Verified | 80.1 | 79.8 | 0.3 | GPT-5.1 Pro |
| HumanEval | 91.1 | 94.6 | 3.5 | o4 Max |
| MATH-500 | 95.1 | 90.6 | 4.5 | GPT-5.1 Pro |
| AIME 2025 | 90.6 | 84.8 | 5.8 | GPT-5.1 Pro |
| LiveCodeBench | 82.2 | 80.6 | 1.6 | GPT-5.1 Pro |
| IFEval | 94.8 | 91.1 | 3.7 | GPT-5.1 Pro |
| TruthfulQA | 86.9 | 87.1 | 0.2 | o4 Max |
| HellaSwag | 93.8 | 91.7 | 2.1 | GPT-5.1 Pro |
| MMMU | 81.6 | 81.9 | 0.3 | o4 Max |
| Arena Elo | 1490.0 | 1486.0 | 4.0 | GPT-5.1 Pro |
Price analysis
On a blended 3:1 input-to-output basis, GPT-5.1 Pro costs about $39.91 per million tokens and o4 Max costs about $38.13. o4 Max is roughly 4% 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.
o4 Max has the larger context window at 2,000,000 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 8, o4 Max wins 4, and 0 are tied. On the index average, GPT-5.1 Pro leads o4 Max by 1.6 points (87.8 versus 86.2).
The price picture favours o4 Max. The context picture favours o4 Max. 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 o4 Max 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.
Choose o4 Max if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 2,000,000-token context window.
- You need the larger 65,536-token output limit.
FAQ
Is GPT-5.1 Pro better than o4 Max?
On the index average, GPT-5.1 Pro leads o4 Max by 1.6 points (87.8 versus 86.2). The better choice depends on price, context and your task. GPT-5.1 Pro wins 8 benchmarks, o4 Max wins 4.
Which is cheaper, GPT-5.1 Pro or o4 Max?
o4 Max is cheaper on a blended 3:1 basis at about $38.13 per million tokens, versus $39.91 for GPT-5.1 Pro.
Which has the larger context window?
o4 Max has the larger context window at 2,000,000 tokens. GPT-5.1 Pro has 200,000 tokens.
Are these models open weights?
GPT-5.1 Pro is proprietary; o4 Max 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 o4 Max for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.