o4 vs Qwen3-Max Pro: which model should you choose?
We compared o4 and Qwen3-Max Pro on price, context window and 12 benchmarks. Qwen3-Max Pro 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 Pro
Qwen3-Max Pro is a frontier model from Alibaba Cloud. It offers a 400,000-token context window, costs $18.87 per million input tokens and $84.39 per million output tokens, and averages 86.2 across the index's benchmark suite.
- Input
- $18.87 / 1M
- Output
- $84.39 / 1M
- Context
- 400,000
- Avg score
- 86.2
- Open weights
- No
Specification comparison
| Spec | o4 | Qwen3-Max Pro | Edge |
|---|---|---|---|
| Input price / 1M | $17.74 | $18.87 | A |
| Output price / 1M | $66.00 | $84.39 | A |
| Context window | 2,000,000 | 400,000 | A |
| Max output | 8,192 | 8,192 | Tie |
| Average score | 85.4 | 86.2 | B |
| Arena Elo | 1469.4 | 1466.4 | A |
| Open weights | No | No | Tie |
Benchmark comparison
o4 wins 4, Qwen3-Max Pro wins 8, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | o4 | Qwen3-Max Pro | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 85.3 | 88.7 | 3.4 | Qwen3-Max Pro |
| GPQA Diamond | 82.3 | 80.0 | 2.3 | o4 |
| SWE-bench Verified | 74.8 | 75.6 | 0.8 | Qwen3-Max Pro |
| HumanEval | 89.6 | 92.1 | 2.5 | Qwen3-Max Pro |
| MATH-500 | 90.5 | 91.8 | 1.3 | Qwen3-Max Pro |
| AIME 2025 | 85.3 | 85.4 | 0.1 | Qwen3-Max Pro |
| LiveCodeBench | 81.4 | 81.0 | 0.4 | o4 |
| IFEval | 92.8 | 93.2 | 0.4 | Qwen3-Max Pro |
| TruthfulQA | 85.0 | 88.6 | 3.6 | Qwen3-Max Pro |
| HellaSwag | 91.0 | 92.4 | 1.4 | Qwen3-Max Pro |
| MMMU | 80.9 | 79.5 | 1.4 | o4 |
| Arena Elo | 1469.4 | 1466.4 | 3.0 | o4 |
Price analysis
On a blended 3:1 input-to-output basis, o4 costs about $29.80 per million tokens and Qwen3-Max Pro costs about $35.25. o4 is roughly 15% cheaper than Qwen3-Max Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
o4 has the larger context window at 2,000,000 tokens, compared with 400,000 for Qwen3-Max Pro. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, o4 wins 4, Qwen3-Max Pro wins 8, and 0 are tied. On the index average, Qwen3-Max Pro leads o4 by 0.8 points (86.2 versus 85.4).
The price picture favours o4. The context picture favours o4. 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 Pro 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.
- You need the larger 2,000,000-token context window.
Choose Qwen3-Max Pro if
- You want the higher average benchmark score in this index.
FAQ
Is o4 better than Qwen3-Max Pro?
On the index average, Qwen3-Max Pro leads o4 by 0.8 points (86.2 versus 85.4). The better choice depends on price, context and your task. o4 wins 4 benchmarks, Qwen3-Max Pro wins 8.
Which is cheaper, o4 or Qwen3-Max Pro?
o4 is cheaper on a blended 3:1 basis at about $29.80 per million tokens, versus $35.25 for Qwen3-Max Pro.
Which has the larger context window?
o4 has the larger context window at 2,000,000 tokens. Qwen3-Max Pro has 400,000 tokens.
Are these models open weights?
o4 is proprietary; Qwen3-Max Pro is proprietary.
Which should I choose for production?
If you need a single default, start with Qwen3-Max Pro 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.