Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3 Pro
83
Qwen3.6-35B-A3B
64
Verified leaderboard positions: Gemini 3 Pro unranked · Qwen3.6-35B-A3B #13
Pick Gemini 3 Pro if you want the stronger benchmark profile. Qwen3.6-35B-A3B only becomes the better choice if you want the stronger reasoning-first profile.
Multimodal
+5.7 difference
Gemini 3 Pro
Qwen3.6-35B-A3B
$null / $null
N/A
109 t/s
N/A
32.65s
N/A
2M
262K
Pick Gemini 3 Pro if you want the stronger benchmark profile. Qwen3.6-35B-A3B only becomes the better choice if you want the stronger reasoning-first profile.
Gemini 3 Pro is clearly ahead on the provisional aggregate, 83 to 64. 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 against 75.3. The single biggest benchmark swing on the page is MMMU-Pro, 81% to 75.3%.
Qwen3.6-35B-A3B is the reasoning model in the pair, while Gemini 3 Pro 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. Gemini 3 Pro gives you the larger context window at 2M, compared with 262K for Qwen3.6-35B-A3B.
Gemini 3 Pro is ahead on BenchLM's provisional leaderboard, 83 to 64. The biggest single separator in this matchup is MMMU-Pro, where the scores are 81% and 75.3%.
Gemini 3 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 81 versus 75.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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