GPT-5.2 Vision vs Qwen3-Max Max: which model should you choose?
We compared GPT-5.2 Vision and Qwen3-Max Max on price, context window and 12 benchmarks. GPT-5.2 Vision has the stronger average benchmark score; Qwen3-Max Max is cheaper on a blended 3:1 basis.
GPT-5.2 Vision
GPT-5.2 Vision is a frontier model from OpenAI. It offers a 1,000,000-token context window, costs $19.03 per million input tokens and $85.72 per million output tokens, and averages 87.4 across the index's benchmark suite.
- Input
- $19.03 / 1M
- Output
- $85.72 / 1M
- Context
- 1,000,000
- Avg score
- 87.4
- 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 | GPT-5.2 Vision | Qwen3-Max Max | Edge |
|---|---|---|---|
| Input price / 1M | $19.03 | $18.53 | B |
| Output price / 1M | $85.72 | $74.05 | B |
| Context window | 1,000,000 | 400,000 | A |
| Max output | 16,384 | 65,536 | B |
| Average score | 87.4 | 85.9 | A |
| Arena Elo | 1484.3 | 1467.7 | A |
| Open weights | No | No | Tie |
Benchmark comparison
GPT-5.2 Vision wins 10, Qwen3-Max Max wins 2, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GPT-5.2 Vision | Qwen3-Max Max | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 89.5 | 85.2 | 4.3 | GPT-5.2 Vision |
| GPQA Diamond | 82.1 | 83.8 | 1.7 | Qwen3-Max Max |
| SWE-bench Verified | 78.8 | 74.3 | 4.5 | GPT-5.2 Vision |
| HumanEval | 91.2 | 90.2 | 1.0 | GPT-5.2 Vision |
| MATH-500 | 92.9 | 92.8 | 0.1 | GPT-5.2 Vision |
| AIME 2025 | 85.7 | 82.7 | 3.0 | GPT-5.2 Vision |
| LiveCodeBench | 83.4 | 82.8 | 0.6 | GPT-5.2 Vision |
| IFEval | 93.9 | 93.7 | 0.2 | GPT-5.2 Vision |
| TruthfulQA | 85.3 | 89.3 | 4.0 | Qwen3-Max Max |
| HellaSwag | 94.6 | 91.4 | 3.2 | GPT-5.2 Vision |
| MMMU | 84.4 | 78.9 | 5.5 | GPT-5.2 Vision |
| Arena Elo | 1484.3 | 1467.7 | 16.6 | GPT-5.2 Vision |
Price analysis
On a blended 3:1 input-to-output basis, GPT-5.2 Vision costs about $35.70 per million tokens and Qwen3-Max Max costs about $32.41. Qwen3-Max Max is roughly 9% cheaper than GPT-5.2 Vision. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GPT-5.2 Vision has the larger context window at 1,000,000 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, GPT-5.2 Vision wins 10, Qwen3-Max Max wins 2, and 0 are tied. On the index average, GPT-5.2 Vision leads Qwen3-Max Max by 1.5 points (87.4 versus 85.9).
The price picture favours Qwen3-Max Max. The context picture favours GPT-5.2 Vision. 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-5.2 Vision 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 GPT-5.2 Vision if
- You want the higher average benchmark score in this index.
- You need the larger 1,000,000-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 GPT-5.2 Vision better than Qwen3-Max Max?
On the index average, GPT-5.2 Vision leads Qwen3-Max Max by 1.5 points (87.4 versus 85.9). The better choice depends on price, context and your task. GPT-5.2 Vision wins 10 benchmarks, Qwen3-Max Max wins 2.
Which is cheaper, GPT-5.2 Vision or Qwen3-Max Max?
Qwen3-Max Max is cheaper on a blended 3:1 basis at about $32.41 per million tokens, versus $35.70 for GPT-5.2 Vision.
Which has the larger context window?
GPT-5.2 Vision has the larger context window at 1,000,000 tokens. Qwen3-Max Max has 400,000 tokens.
Are these models open weights?
GPT-5.2 Vision is proprietary; Qwen3-Max Max is proprietary.
Which should I choose for production?
If you need a single default, start with GPT-5.2 Vision 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.