GPT-5.1 vs Qwen3-Max Reasoning: which model should you choose?
We compared GPT-5.1 and Qwen3-Max Reasoning on price, context window and 12 benchmarks. GPT-5.1 has the stronger average benchmark score; GPT-5.1 is cheaper on a blended 3:1 basis.
GPT-5.1
GPT-5.1 is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $19.01 per million input tokens and $69.84 per million output tokens, and averages 86.0 across the index's benchmark suite.
- Input
- $19.01 / 1M
- Output
- $69.84 / 1M
- Context
- 2,000,000
- Avg score
- 86.0
- 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 | GPT-5.1 | Qwen3-Max Reasoning | Edge |
|---|---|---|---|
| Input price / 1M | $19.01 | $18.12 | B |
| Output price / 1M | $69.84 | $81.94 | A |
| Context window | 2,000,000 | 2,000,000 | Tie |
| Max output | 128,000 | 8,192 | A |
| Average score | 86.0 | 85.9 | A |
| Arena Elo | 1462.5 | 1461.0 | A |
| Open weights | No | No | Tie |
Benchmark comparison
GPT-5.1 wins 8, Qwen3-Max Reasoning wins 4, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GPT-5.1 | Qwen3-Max Reasoning | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 86.1 | 88.1 | 2.0 | Qwen3-Max Reasoning |
| GPQA Diamond | 82.3 | 79.8 | 2.5 | GPT-5.1 |
| SWE-bench Verified | 76.1 | 75.3 | 0.8 | GPT-5.1 |
| HumanEval | 90.6 | 92.6 | 2.0 | Qwen3-Max Reasoning |
| MATH-500 | 90.5 | 93.0 | 2.5 | Qwen3-Max Reasoning |
| AIME 2025 | 85.6 | 83.1 | 2.5 | GPT-5.1 |
| LiveCodeBench | 78.9 | 78.0 | 0.9 | GPT-5.1 |
| IFEval | 90.9 | 92.2 | 1.3 | Qwen3-Max Reasoning |
| TruthfulQA | 89.2 | 88.8 | 0.4 | GPT-5.1 |
| HellaSwag | 92.2 | 91.5 | 0.7 | GPT-5.1 |
| MMMU | 83.3 | 82.3 | 1.0 | GPT-5.1 |
| Arena Elo | 1462.5 | 1461.0 | 1.5 | GPT-5.1 |
Price analysis
On a blended 3:1 input-to-output basis, GPT-5.1 costs about $31.72 per million tokens and Qwen3-Max Reasoning costs about $34.08. GPT-5.1 is roughly 7% cheaper than Qwen3-Max Reasoning. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 2,000,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, GPT-5.1 wins 8, Qwen3-Max Reasoning wins 4, and 0 are tied. On the index average, GPT-5.1 leads Qwen3-Max Reasoning by 0.1 points (86.0 versus 85.9).
The price picture favours GPT-5.1. The context picture is effectively a tie. 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 GPT-5.1 for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose GPT-5.1 if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
- You need the larger 128,000-token output limit.
Choose Qwen3-Max Reasoning if
- You prefer Alibaba Cloud's tooling or already use it.
FAQ
Is GPT-5.1 better than Qwen3-Max Reasoning?
On the index average, GPT-5.1 leads Qwen3-Max Reasoning by 0.1 points (86.0 versus 85.9). The better choice depends on price, context and your task. GPT-5.1 wins 8 benchmarks, Qwen3-Max Reasoning wins 4.
Which is cheaper, GPT-5.1 or Qwen3-Max Reasoning?
GPT-5.1 is cheaper on a blended 3:1 basis at about $31.72 per million tokens, versus $34.08 for Qwen3-Max Reasoning.
Which has the larger context window?
Both models list a 2,000,000-token context window.
Are these models open weights?
GPT-5.1 is proprietary; Qwen3-Max Reasoning is proprietary.
Which should I choose for production?
If you need a single default, start with GPT-5.1 for quality-sensitive work, and check whether its price holds at your expected volume before committing.