GPT-5.1 vs Qwen3-Max Pro: which model should you choose?
We compared GPT-5.1 and Qwen3-Max Pro on price, context window and 12 benchmarks. Qwen3-Max Pro 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 Pro
Qwen3-Max Pro is a frontier model from Alibaba Cloud. It offers a 400,000-token context window, costs $18.87 per million input tokens and $84.39 per million output tokens, and averages 86.2 across the index's benchmark suite.
- Input
- $18.87 / 1M
- Output
- $84.39 / 1M
- Context
- 400,000
- Avg score
- 86.2
- Open weights
- No
Specification comparison
| Spec | GPT-5.1 | Qwen3-Max Pro | Edge |
|---|---|---|---|
| Input price / 1M | $19.01 | $18.87 | B |
| Output price / 1M | $69.84 | $84.39 | A |
| Context window | 2,000,000 | 400,000 | A |
| Max output | 128,000 | 8,192 | A |
| Average score | 86.0 | 86.2 | B |
| Arena Elo | 1462.5 | 1466.4 | B |
| Open weights | No | No | Tie |
Benchmark comparison
GPT-5.1 wins 5, Qwen3-Max Pro wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GPT-5.1 | Qwen3-Max Pro | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 86.1 | 88.7 | 2.6 | Qwen3-Max Pro |
| GPQA Diamond | 82.3 | 80.0 | 2.3 | GPT-5.1 |
| SWE-bench Verified | 76.1 | 75.6 | 0.5 | GPT-5.1 |
| HumanEval | 90.6 | 92.1 | 1.5 | Qwen3-Max Pro |
| MATH-500 | 90.5 | 91.8 | 1.3 | Qwen3-Max Pro |
| AIME 2025 | 85.6 | 85.4 | 0.2 | GPT-5.1 |
| LiveCodeBench | 78.9 | 81.0 | 2.1 | Qwen3-Max Pro |
| IFEval | 90.9 | 93.2 | 2.3 | Qwen3-Max Pro |
| TruthfulQA | 89.2 | 88.6 | 0.6 | GPT-5.1 |
| HellaSwag | 92.2 | 92.4 | 0.2 | Qwen3-Max Pro |
| MMMU | 83.3 | 79.5 | 3.8 | GPT-5.1 |
| Arena Elo | 1462.5 | 1466.4 | 3.9 | Qwen3-Max Pro |
Price analysis
On a blended 3:1 input-to-output basis, GPT-5.1 costs about $31.72 per million tokens and Qwen3-Max Pro costs about $35.25. GPT-5.1 is roughly 10% cheaper than Qwen3-Max Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GPT-5.1 has the larger context window at 2,000,000 tokens, compared with 400,000 for Qwen3-Max Pro. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, GPT-5.1 wins 5, Qwen3-Max Pro wins 7, and 0 are tied. On the index average, Qwen3-Max Pro leads GPT-5.1 by 0.2 points (86.2 versus 86.0).
The price picture favours GPT-5.1. The context picture favours GPT-5.1. 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 Pro for quality-sensitive work and GPT-5.1 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose GPT-5.1 if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 2,000,000-token context window.
- You need the larger 128,000-token output limit.
Choose Qwen3-Max Pro if
- You want the higher average benchmark score in this index.
FAQ
Is GPT-5.1 better than Qwen3-Max Pro?
On the index average, Qwen3-Max Pro leads GPT-5.1 by 0.2 points (86.2 versus 86.0). The better choice depends on price, context and your task. GPT-5.1 wins 5 benchmarks, Qwen3-Max Pro wins 7.
Which is cheaper, GPT-5.1 or Qwen3-Max Pro?
GPT-5.1 is cheaper on a blended 3:1 basis at about $31.72 per million tokens, versus $35.25 for Qwen3-Max Pro.
Which has the larger context window?
GPT-5.1 has the larger context window at 2,000,000 tokens. Qwen3-Max Pro has 400,000 tokens.
Are these models open weights?
GPT-5.1 is proprietary; Qwen3-Max Pro is proprietary.
Which should I choose for production?
If you need a single default, start with Qwen3-Max Pro for quality-sensitive work and GPT-5.1 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.