Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Qwen2.5-VL-32B is clearly ahead on the aggregate, 41 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 nano is the reasoning model in the pair, while Qwen2.5-VL-32B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-5 nano gives you the larger context window at 400K, compared with 32K for Qwen2.5-VL-32B.
Pick Qwen2.5-VL-32B if you want the stronger benchmark profile. GPT-5 nano only becomes the better choice if mathematics is the priority or you need the larger 400K context window.
Qwen2.5-VL-32B
36.3
GPT-5 nano
71.2
Qwen2.5-VL-32B
44.1
GPT-5 nano
85.2
Qwen2.5-VL-32B is ahead overall, 41 to 31. The biggest single separator in this matchup is AIME 2025, where the scores are 44 and 85.2.
GPT-5 nano has the edge for knowledge tasks in this comparison, averaging 71.2 versus 36.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5 nano has the edge for math in this comparison, averaging 85.2 versus 44.1. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
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