o4 vs Qwen3-Max Reasoning: which model should you choose?
We compared o4 and Qwen3-Max Reasoning on price, context window and 12 benchmarks. Qwen3-Max Reasoning has the stronger average benchmark score; o4 is cheaper on a blended 3:1 basis.
o4
o4 is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $17.74 per million input tokens and $66.00 per million output tokens, and averages 85.4 across the index's benchmark suite.
- Input
- $17.74 / 1M
- Output
- $66.00 / 1M
- Context
- 2,000,000
- Avg score
- 85.4
- Open weights
- No
Qwen3-Max Reasoning
Qwen3-Max Reasoning is a frontier model from Alibaba Cloud. It offers a 2,000,000-token context window, costs $18.12 per million input tokens and $81.94 per million output tokens, and averages 85.9 across the index's benchmark suite.
- Input
- $18.12 / 1M
- Output
- $81.94 / 1M
- Context
- 2,000,000
- Avg score
- 85.9
- Open weights
- No
Specification comparison
| Spec | o4 | Qwen3-Max Reasoning | Edge |
|---|---|---|---|
| Input price / 1M | $17.74 | $18.12 | A |
| Output price / 1M | $66.00 | $81.94 | A |
| Context window | 2,000,000 | 2,000,000 | Tie |
| Max output | 8,192 | 8,192 | Tie |
| Average score | 85.4 | 85.9 | B |
| Arena Elo | 1469.4 | 1461.0 | A |
| Open weights | No | No | Tie |
Benchmark comparison
o4 wins 5, Qwen3-Max Reasoning wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | o4 | Qwen3-Max Reasoning | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 85.3 | 88.1 | 2.8 | Qwen3-Max Reasoning |
| GPQA Diamond | 82.3 | 79.8 | 2.5 | o4 |
| SWE-bench Verified | 74.8 | 75.3 | 0.5 | Qwen3-Max Reasoning |
| HumanEval | 89.6 | 92.6 | 3.0 | Qwen3-Max Reasoning |
| MATH-500 | 90.5 | 93.0 | 2.5 | Qwen3-Max Reasoning |
| AIME 2025 | 85.3 | 83.1 | 2.2 | o4 |
| LiveCodeBench | 81.4 | 78.0 | 3.4 | o4 |
| IFEval | 92.8 | 92.2 | 0.6 | o4 |
| TruthfulQA | 85.0 | 88.8 | 3.8 | Qwen3-Max Reasoning |
| HellaSwag | 91.0 | 91.5 | 0.5 | Qwen3-Max Reasoning |
| MMMU | 80.9 | 82.3 | 1.4 | Qwen3-Max Reasoning |
| Arena Elo | 1469.4 | 1461.0 | 8.4 | o4 |
Price analysis
On a blended 3:1 input-to-output basis, o4 costs about $29.80 per million tokens and Qwen3-Max Reasoning costs about $34.08. o4 is roughly 13% cheaper than Qwen3-Max Reasoning. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 2,000,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, o4 wins 5, Qwen3-Max Reasoning wins 7, and 0 are tied. On the index average, Qwen3-Max Reasoning leads o4 by 0.5 points (85.9 versus 85.4).
The price picture favours o4. The context picture is effectively a tie. 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 Qwen3-Max Reasoning for quality-sensitive work and o4 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose o4 if
- Unit cost matters and you want the cheaper blended price.
Choose Qwen3-Max Reasoning if
- You want the higher average benchmark score in this index.
FAQ
Is o4 better than Qwen3-Max Reasoning?
On the index average, Qwen3-Max Reasoning leads o4 by 0.5 points (85.9 versus 85.4). The better choice depends on price, context and your task. o4 wins 5 benchmarks, Qwen3-Max Reasoning wins 7.
Which is cheaper, o4 or Qwen3-Max Reasoning?
o4 is cheaper on a blended 3:1 basis at about $29.80 per million tokens, versus $34.08 for Qwen3-Max Reasoning.
Which has the larger context window?
Both models list a 2,000,000-token context window.
Are these models open weights?
o4 is proprietary; Qwen3-Max Reasoning is proprietary.
Which should I choose for production?
If you need a single default, start with Qwen3-Max Reasoning for quality-sensitive work and o4 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.