o3 Reasoning vs Qwen3-Max Reasoning: which model should you choose?
We compared o3 Reasoning and Qwen3-Max Reasoning on price, context window and 12 benchmarks. Qwen3-Max Reasoning has the stronger average benchmark score; o3 Reasoning is cheaper on a blended 3:1 basis.
o3 Reasoning
o3 Reasoning is a frontier model from OpenAI. It offers a 200,000-token context window, costs $18.07 per million input tokens and $70.65 per million output tokens, and averages 85.3 across the index's benchmark suite.
- Input
- $18.07 / 1M
- Output
- $70.65 / 1M
- Context
- 200,000
- Avg score
- 85.3
- 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 | o3 Reasoning | Qwen3-Max Reasoning | Edge |
|---|---|---|---|
| Input price / 1M | $18.07 | $18.12 | A |
| Output price / 1M | $70.65 | $81.94 | A |
| Context window | 200,000 | 2,000,000 | B |
| Max output | 16,384 | 8,192 | A |
| Average score | 85.3 | 85.9 | B |
| Arena Elo | 1456.9 | 1461.0 | B |
| Open weights | No | No | Tie |
Benchmark comparison
o3 Reasoning wins 1, Qwen3-Max Reasoning wins 10, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | o3 Reasoning | Qwen3-Max Reasoning | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 87.7 | 88.1 | 0.4 | Qwen3-Max Reasoning |
| GPQA Diamond | 79.6 | 79.8 | 0.2 | Qwen3-Max Reasoning |
| SWE-bench Verified | 74.1 | 75.3 | 1.2 | Qwen3-Max Reasoning |
| HumanEval | 91.3 | 92.6 | 1.3 | Qwen3-Max Reasoning |
| MATH-500 | 92.0 | 93.0 | 1.0 | Qwen3-Max Reasoning |
| AIME 2025 | 80.5 | 83.1 | 2.6 | Qwen3-Max Reasoning |
| LiveCodeBench | 82.7 | 78.0 | 4.7 | o3 Reasoning |
| IFEval | 90.6 | 92.2 | 1.6 | Qwen3-Max Reasoning |
| TruthfulQA | 86.5 | 88.8 | 2.3 | Qwen3-Max Reasoning |
| HellaSwag | 90.9 | 91.5 | 0.6 | Qwen3-Max Reasoning |
| MMMU | 82.3 | 82.3 | 0.0 | Tie |
| Arena Elo | 1456.9 | 1461.0 | 4.1 | Qwen3-Max Reasoning |
Price analysis
On a blended 3:1 input-to-output basis, o3 Reasoning costs about $31.22 per million tokens and Qwen3-Max Reasoning costs about $34.08. o3 Reasoning is roughly 8% cheaper than Qwen3-Max Reasoning. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Qwen3-Max Reasoning has the larger context window at 2,000,000 tokens, compared with 200,000 for o3 Reasoning. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, o3 Reasoning wins 1, Qwen3-Max Reasoning wins 10, and 1 are tied. On the index average, Qwen3-Max Reasoning leads o3 Reasoning by 0.6 points (85.9 versus 85.3).
The price picture favours o3 Reasoning. The context picture favours Qwen3-Max Reasoning. 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 o3 Reasoning for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose o3 Reasoning if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 16,384-token output limit.
Choose Qwen3-Max Reasoning if
- You want the higher average benchmark score in this index.
- You need the larger 2,000,000-token context window.
FAQ
Is o3 Reasoning better than Qwen3-Max Reasoning?
On the index average, Qwen3-Max Reasoning leads o3 Reasoning by 0.6 points (85.9 versus 85.3). The better choice depends on price, context and your task. o3 Reasoning wins 1 benchmarks, Qwen3-Max Reasoning wins 10.
Which is cheaper, o3 Reasoning or Qwen3-Max Reasoning?
o3 Reasoning is cheaper on a blended 3:1 basis at about $31.22 per million tokens, versus $34.08 for Qwen3-Max Reasoning.
Which has the larger context window?
Qwen3-Max Reasoning has the larger context window at 2,000,000 tokens. o3 Reasoning has 200,000 tokens.
Are these models open weights?
o3 Reasoning 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 o3 Reasoning for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.