Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3.1 Flash-Lite
48
Qwen3.5 397B
63
Verified leaderboard positions: Gemini 3.1 Flash-Lite unranked · Qwen3.5 397B #19
Pick Qwen3.5 397B if you want the stronger benchmark profile. Gemini 3.1 Flash-Lite only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Multimodal
+6.4 difference
Gemini 3.1 Flash-Lite
Qwen3.5 397B
$0.25 / $1.5
$0.6 / $3.6
205 t/s
96 t/s
7.50s
2.44s
1M
128K
Pick Qwen3.5 397B if you want the stronger benchmark profile. Gemini 3.1 Flash-Lite only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Qwen3.5 397B is clearly ahead on the provisional aggregate, 63 to 48. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5 397B's sharpest advantage is in multimodal & grounded, where it averages 79.6 against 73.2. The single biggest benchmark swing on the page is CharXiv, 73.2% to 80.8%.
Qwen3.5 397B is also the more expensive model on tokens at $0.60 input / $3.60 output per 1M tokens, versus $0.25 input / $1.50 output per 1M tokens for Gemini 3.1 Flash-Lite. That is roughly 2.4x on output cost alone. Gemini 3.1 Flash-Lite gives you the larger context window at 1M, compared with 128K for Qwen3.5 397B.
Qwen3.5 397B is ahead on BenchLM's provisional leaderboard, 63 to 48. The biggest single separator in this matchup is CharXiv, where the scores are 73.2% and 80.8%.
Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 73.2. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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