o4 vs Qwen3-Max Turbo: which model should you choose?
We compared o4 and Qwen3-Max Turbo on price, context window and 12 benchmarks. o4 has the stronger average benchmark score; Qwen3-Max Turbo 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 Turbo
Qwen3-Max Turbo is a frontier model from Alibaba Cloud. It offers a 1,000,000-token context window, costs $17.70 per million input tokens and $63.95 per million output tokens, and averages 84.7 across the index's benchmark suite.
- Input
- $17.70 / 1M
- Output
- $63.95 / 1M
- Context
- 1,000,000
- Avg score
- 84.7
- Open weights
- No
Specification comparison
| Spec | o4 | Qwen3-Max Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $17.74 | $17.70 | B |
| Output price / 1M | $66.00 | $63.95 | B |
| Context window | 2,000,000 | 1,000,000 | A |
| Max output | 8,192 | 128,000 | B |
| Average score | 85.4 | 84.7 | A |
| Arena Elo | 1469.4 | 1456.9 | A |
| Open weights | No | No | Tie |
Benchmark comparison
o4 wins 7, Qwen3-Max Turbo wins 5, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | o4 | Qwen3-Max Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 85.3 | 86.8 | 1.5 | Qwen3-Max Turbo |
| GPQA Diamond | 82.3 | 78.3 | 4.0 | o4 |
| SWE-bench Verified | 74.8 | 75.9 | 1.1 | Qwen3-Max Turbo |
| HumanEval | 89.6 | 92.5 | 2.9 | Qwen3-Max Turbo |
| MATH-500 | 90.5 | 91.9 | 1.4 | Qwen3-Max Turbo |
| AIME 2025 | 85.3 | 81.2 | 4.1 | o4 |
| LiveCodeBench | 81.4 | 76.8 | 4.6 | o4 |
| IFEval | 92.8 | 92.1 | 0.7 | o4 |
| TruthfulQA | 85.0 | 86.3 | 1.3 | Qwen3-Max Turbo |
| HellaSwag | 91.0 | 90.8 | 0.2 | o4 |
| MMMU | 80.9 | 78.8 | 2.1 | o4 |
| Arena Elo | 1469.4 | 1456.9 | 12.5 | o4 |
Price analysis
On a blended 3:1 input-to-output basis, o4 costs about $29.80 per million tokens and Qwen3-Max Turbo costs about $29.26. Qwen3-Max Turbo is roughly 2% cheaper than o4. 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 1,000,000 for Qwen3-Max Turbo. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, o4 wins 7, Qwen3-Max Turbo wins 5, and 0 are tied. On the index average, o4 leads Qwen3-Max Turbo by 0.7 points (85.4 versus 84.7).
The price picture favours Qwen3-Max Turbo. 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 o4 for quality-sensitive work and Qwen3-Max Turbo for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose o4 if
- You want the higher average benchmark score in this index.
- You need the larger 2,000,000-token context window.
Choose Qwen3-Max Turbo if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 128,000-token output limit.
FAQ
Is o4 better than Qwen3-Max Turbo?
On the index average, o4 leads Qwen3-Max Turbo by 0.7 points (85.4 versus 84.7). The better choice depends on price, context and your task. o4 wins 7 benchmarks, Qwen3-Max Turbo wins 5.
Which is cheaper, o4 or Qwen3-Max Turbo?
Qwen3-Max Turbo is cheaper on a blended 3:1 basis at about $29.26 per million tokens, versus $29.80 for o4.
Which has the larger context window?
o4 has the larger context window at 2,000,000 tokens. Qwen3-Max Turbo has 1,000,000 tokens.
Are these models open weights?
o4 is proprietary; Qwen3-Max Turbo is proprietary.
Which should I choose for production?
If you need a single default, start with o4 for quality-sensitive work and Qwen3-Max Turbo for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.