o4 vs Qwen3-Max Max: which model should you choose?
We compared o4 and Qwen3-Max Max on price, context window and 12 benchmarks. Qwen3-Max Max 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 Max
Qwen3-Max Max is a frontier model from Alibaba Cloud. It offers a 400,000-token context window, costs $18.53 per million input tokens and $74.05 per million output tokens, and averages 85.9 across the index's benchmark suite.
- Input
- $18.53 / 1M
- Output
- $74.05 / 1M
- Context
- 400,000
- Avg score
- 85.9
- Open weights
- No
Specification comparison
| Spec | o4 | Qwen3-Max Max | Edge |
|---|---|---|---|
| Input price / 1M | $17.74 | $18.53 | A |
| Output price / 1M | $66.00 | $74.05 | A |
| Context window | 2,000,000 | 400,000 | A |
| Max output | 8,192 | 65,536 | B |
| Average score | 85.4 | 85.9 | B |
| Arena Elo | 1469.4 | 1467.7 | A |
| Open weights | No | No | Tie |
Benchmark comparison
o4 wins 5, Qwen3-Max Max wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | o4 | Qwen3-Max Max | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 85.3 | 85.2 | 0.1 | o4 |
| GPQA Diamond | 82.3 | 83.8 | 1.5 | Qwen3-Max Max |
| SWE-bench Verified | 74.8 | 74.3 | 0.5 | o4 |
| HumanEval | 89.6 | 90.2 | 0.6 | Qwen3-Max Max |
| MATH-500 | 90.5 | 92.8 | 2.3 | Qwen3-Max Max |
| AIME 2025 | 85.3 | 82.7 | 2.6 | o4 |
| LiveCodeBench | 81.4 | 82.8 | 1.4 | Qwen3-Max Max |
| IFEval | 92.8 | 93.7 | 0.9 | Qwen3-Max Max |
| TruthfulQA | 85.0 | 89.3 | 4.3 | Qwen3-Max Max |
| HellaSwag | 91.0 | 91.4 | 0.4 | Qwen3-Max Max |
| MMMU | 80.9 | 78.9 | 2.0 | o4 |
| Arena Elo | 1469.4 | 1467.7 | 1.7 | o4 |
Price analysis
On a blended 3:1 input-to-output basis, o4 costs about $29.80 per million tokens and Qwen3-Max Max costs about $32.41. o4 is roughly 8% cheaper than Qwen3-Max Max. 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 Max. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, o4 wins 5, Qwen3-Max Max wins 7, and 0 are tied. On the index average, Qwen3-Max Max leads o4 by 0.5 points (85.9 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 Max 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 Max if
- You want the higher average benchmark score in this index.
- You need the larger 65,536-token output limit.
FAQ
Is o4 better than Qwen3-Max Max?
On the index average, Qwen3-Max Max 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 Max wins 7.
Which is cheaper, o4 or Qwen3-Max Max?
o4 is cheaper on a blended 3:1 basis at about $29.80 per million tokens, versus $32.41 for Qwen3-Max Max.
Which has the larger context window?
o4 has the larger context window at 2,000,000 tokens. Qwen3-Max Max has 400,000 tokens.
Are these models open weights?
o4 is proprietary; Qwen3-Max Max is proprietary.
Which should I choose for production?
If you need a single default, start with Qwen3-Max Max 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.