Head-to-head comparison across 2 benchmark categories
Qwen2.5-VL-32B
50
Qwen3.6 Plus
69
Pick Qwen3.6 Plus if you want the stronger benchmark profile. Qwen2.5-VL-32B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+5.2 difference
Multimodal
+29.3 difference
Qwen2.5-VL-32B
Qwen3.6 Plus
$0 / $0
$0 / $0
N/A
N/A
N/A
N/A
32K
1M
Pick Qwen3.6 Plus if you want the stronger benchmark profile. Qwen2.5-VL-32B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Qwen3.6 Plus is clearly ahead on the aggregate, 69 to 50. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6 Plus's sharpest advantage is in multimodal & grounded, where it averages 78.8 against 49.5. The single biggest benchmark swing on the page is GPQA, 46% to 90.4%.
Qwen3.6 Plus 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. Qwen3.6 Plus gives you the larger context window at 1M, compared with 32K for Qwen2.5-VL-32B.
Qwen3.6 Plus is ahead overall, 69 to 50. The biggest single separator in this matchup is GPQA, where the scores are 46% and 90.4%.
Qwen3.6 Plus has the edge for knowledge tasks in this comparison, averaging 66 versus 60.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen3.6 Plus has the edge for multimodal and grounded tasks in this comparison, averaging 78.8 versus 49.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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