o4 Turbo vs Qwen3-Max Max: which model should you choose?
We compared o4 Turbo and Qwen3-Max Max on price, context window and 12 benchmarks. o4 Turbo has the stronger average benchmark score; Qwen3-Max Max is cheaper on a blended 3:1 basis.
o4 Turbo
o4 Turbo is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $19.34 per million input tokens and $82.19 per million output tokens, and averages 86.6 across the index's benchmark suite.
- Input
- $19.34 / 1M
- Output
- $82.19 / 1M
- Context
- 2,000,000
- Avg score
- 86.6
- 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 Turbo | Qwen3-Max Max | Edge |
|---|---|---|---|
| Input price / 1M | $19.34 | $18.53 | B |
| Output price / 1M | $82.19 | $74.05 | B |
| Context window | 2,000,000 | 400,000 | A |
| Max output | 8,192 | 65,536 | B |
| Average score | 86.6 | 85.9 | A |
| Arena Elo | 1468.1 | 1467.7 | A |
| Open weights | No | No | Tie |
Benchmark comparison
o4 Turbo wins 7, Qwen3-Max Max wins 5, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | o4 Turbo | Qwen3-Max Max | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 88.1 | 85.2 | 2.9 | o4 Turbo |
| GPQA Diamond | 84.8 | 83.8 | 1.0 | o4 Turbo |
| SWE-bench Verified | 78.4 | 74.3 | 4.1 | o4 Turbo |
| HumanEval | 91.0 | 90.2 | 0.8 | o4 Turbo |
| MATH-500 | 91.7 | 92.8 | 1.1 | Qwen3-Max Max |
| AIME 2025 | 85.9 | 82.7 | 3.2 | o4 Turbo |
| LiveCodeBench | 80.1 | 82.8 | 2.7 | Qwen3-Max Max |
| IFEval | 92.6 | 93.7 | 1.1 | Qwen3-Max Max |
| TruthfulQA | 88.8 | 89.3 | 0.5 | Qwen3-Max Max |
| HellaSwag | 91.3 | 91.4 | 0.1 | Qwen3-Max Max |
| MMMU | 79.6 | 78.9 | 0.7 | o4 Turbo |
| Arena Elo | 1468.1 | 1467.7 | 0.4 | o4 Turbo |
Price analysis
On a blended 3:1 input-to-output basis, o4 Turbo costs about $35.05 per million tokens and Qwen3-Max Max costs about $32.41. Qwen3-Max Max is roughly 8% cheaper than o4 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
o4 Turbo 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 Turbo wins 7, Qwen3-Max Max wins 5, and 0 are tied. On the index average, o4 Turbo leads Qwen3-Max Max by 0.7 points (86.6 versus 85.9).
The price picture favours Qwen3-Max Max. The context picture favours o4 Turbo. 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 Turbo for quality-sensitive work and Qwen3-Max Max for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose o4 Turbo if
- You want the higher average benchmark score in this index.
- You need the larger 2,000,000-token context window.
Choose Qwen3-Max Max if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 65,536-token output limit.
FAQ
Is o4 Turbo better than Qwen3-Max Max?
On the index average, o4 Turbo leads Qwen3-Max Max by 0.7 points (86.6 versus 85.9). The better choice depends on price, context and your task. o4 Turbo wins 7 benchmarks, Qwen3-Max Max wins 5.
Which is cheaper, o4 Turbo or Qwen3-Max Max?
Qwen3-Max Max is cheaper on a blended 3:1 basis at about $32.41 per million tokens, versus $35.05 for o4 Turbo.
Which has the larger context window?
o4 Turbo has the larger context window at 2,000,000 tokens. Qwen3-Max Max has 400,000 tokens.
Are these models open weights?
o4 Turbo is proprietary; Qwen3-Max Max is proprietary.
Which should I choose for production?
If you need a single default, start with o4 Turbo for quality-sensitive work and Qwen3-Max Max for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.