o4 Max vs o4 Reasoning: which model should you choose?
We compared o4 Max and o4 Reasoning on price, context window and 12 benchmarks. o4 Reasoning has the stronger average benchmark score; o4 Max is cheaper on a blended 3:1 basis.
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
o4 Reasoning
o4 Reasoning is a frontier model from OpenAI. It offers a 1,000,000-token context window, costs $19.69 per million input tokens and $103.53 per million output tokens, and averages 87.5 across the index's benchmark suite.
- Input
- $19.69 / 1M
- Output
- $103.53 / 1M
- Context
- 1,000,000
- Avg score
- 87.5
- Open weights
- No
Specification comparison
| Spec | o4 Max | o4 Reasoning | Edge |
|---|---|---|---|
| Input price / 1M | $19.51 | $19.69 | A |
| Output price / 1M | $93.98 | $103.53 | A |
| Context window | 2,000,000 | 1,000,000 | A |
| Max output | 65,536 | 128,000 | B |
| Average score | 86.2 | 87.5 | B |
| Arena Elo | 1486.0 | 1472.2 | A |
| Open weights | No | No | Tie |
Benchmark comparison
o4 Max wins 5, o4 Reasoning wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | o4 Max | o4 Reasoning | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 86.3 | 86.1 | 0.2 | o4 Max |
| GPQA Diamond | 80.1 | 84.0 | 3.9 | o4 Reasoning |
| SWE-bench Verified | 79.8 | 76.4 | 3.4 | o4 Max |
| HumanEval | 94.6 | 90.2 | 4.4 | o4 Max |
| MATH-500 | 90.6 | 94.8 | 4.2 | o4 Reasoning |
| AIME 2025 | 84.8 | 90.3 | 5.5 | o4 Reasoning |
| LiveCodeBench | 80.6 | 83.4 | 2.8 | o4 Reasoning |
| IFEval | 91.1 | 94.5 | 3.4 | o4 Reasoning |
| TruthfulQA | 87.1 | 89.0 | 1.9 | o4 Reasoning |
| HellaSwag | 91.7 | 92.4 | 0.7 | o4 Reasoning |
| MMMU | 81.9 | 81.8 | 0.1 | o4 Max |
| Arena Elo | 1486.0 | 1472.2 | 13.8 | o4 Max |
Price analysis
On a blended 3:1 input-to-output basis, o4 Max costs about $38.13 per million tokens and o4 Reasoning costs about $40.65. o4 Max is roughly 6% cheaper than o4 Reasoning. 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 1,000,000 for o4 Reasoning. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, o4 Max wins 5, o4 Reasoning wins 7, and 0 are tied. On the index average, o4 Reasoning leads o4 Max by 1.3 points (87.5 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 o4 Reasoning 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 o4 Max if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 2,000,000-token context window.
Choose o4 Reasoning if
- You want the higher average benchmark score in this index.
- You need the larger 128,000-token output limit.
FAQ
Is o4 Max better than o4 Reasoning?
On the index average, o4 Reasoning leads o4 Max by 1.3 points (87.5 versus 86.2). The better choice depends on price, context and your task. o4 Max wins 5 benchmarks, o4 Reasoning wins 7.
Which is cheaper, o4 Max or o4 Reasoning?
o4 Max is cheaper on a blended 3:1 basis at about $38.13 per million tokens, versus $40.65 for o4 Reasoning.
Which has the larger context window?
o4 Max has the larger context window at 2,000,000 tokens. o4 Reasoning has 1,000,000 tokens.
Are these models open weights?
o4 Max is proprietary; o4 Reasoning is proprietary.
Which should I choose for production?
If you need a single default, start with o4 Reasoning 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.