Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3.1 Pro
93
Qwen3.5 397B
66
Verified leaderboard positions: Gemini 3.1 Pro unranked · Qwen3.5 397B #10
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if you want the cheaper token bill.
Reasoning
+13.9 difference
Multimodal
+4.9 difference
Gemini 3.1 Pro
Qwen3.5 397B
$1.25 / $5
$0 / $0
109 t/s
96 t/s
29.71s
2.44s
1M
128K
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if you want the cheaper token bill.
Gemini 3.1 Pro is clearly ahead on the provisional aggregate, 93 to 66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.1 Pro's sharpest advantage is in reasoning, where it averages 77.1 against 63.2. The single biggest benchmark swing on the page is MMMU-Pro, 83.9% to 79%.
Gemini 3.1 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5 397B. That is roughly Infinityx on output cost alone. Gemini 3.1 Pro gives you the larger context window at 1M, compared with 128K for Qwen3.5 397B.
Gemini 3.1 Pro is ahead on BenchLM's provisional leaderboard, 93 to 66. The biggest single separator in this matchup is MMMU-Pro, where the scores are 83.9% and 79%.
Gemini 3.1 Pro has the edge for reasoning in this comparison, averaging 77.1 versus 63.2. Qwen3.5 397B stays close enough that the answer can still flip depending on your workload.
Gemini 3.1 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 83.9 versus 79. Inside this category, ScreenSpot Pro is the benchmark that creates the most daylight between them.
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