Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3 Pro
81
Qwen3.5 397B
63
Verified leaderboard positions: Gemini 3 Pro unranked · Qwen3.5 397B #19
Pick Gemini 3 Pro if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if reasoning is the priority or you want the cheaper token bill.
Reasoning
+32.1 difference
Multimodal
+1.5 difference
Gemini 3 Pro
Qwen3.5 397B
$2 / $12
$0.6 / $3.6
109 t/s
96 t/s
32.65s
2.44s
2M
128K
Pick Gemini 3 Pro if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if reasoning is the priority or you want the cheaper token bill.
Gemini 3 Pro is clearly ahead on the provisional aggregate, 81 to 63. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3 Pro's sharpest advantage is in multimodal & grounded, where it averages 81.1 against 79.6. The single biggest benchmark swing on the page is MMMU-Pro, 81% to 79%. Qwen3.5 397B does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
Gemini 3 Pro is also the more expensive model on tokens at $2.00 input / $12.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. That is roughly 3.3x on output cost alone. Gemini 3 Pro gives you the larger context window at 2M, compared with 128K for Qwen3.5 397B.
Gemini 3 Pro is ahead on BenchLM's provisional leaderboard, 81 to 63. The biggest single separator in this matchup is MMMU-Pro, where the scores are 81% and 79%.
Qwen3.5 397B has the edge for reasoning in this comparison, averaging 63.2 versus 31.1. Inside this category, AA-LCR is the benchmark that creates the most daylight between them.
Gemini 3 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 81.1 versus 79.6. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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