Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3.5 Flash
88
Qwen3 235B 2507
33
Verified leaderboard positions: Gemini 3.5 Flash #7 · Qwen3 235B 2507 unranked
Pick Gemini 3.5 Flash if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Knowledge
+18.2 difference
Gemini 3.5 Flash
Qwen3 235B 2507
$1.5 / $9
$0 / $0
284.2 t/s
N/A
18.55s
N/A
1M
128K
Pick Gemini 3.5 Flash if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Gemini 3.5 Flash is clearly ahead on the provisional aggregate, 88 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.5 Flash is also the more expensive model on tokens at $1.50 input / $9.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3 235B 2507. That is roughly Infinityx on output cost alone. Gemini 3.5 Flash is the reasoning model in the pair, while Qwen3 235B 2507 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 3.5 Flash gives you the larger context window at 1M, compared with 128K for Qwen3 235B 2507.
Gemini 3.5 Flash is ahead on BenchLM's provisional leaderboard, 88 to 33. The biggest single separator in this matchup is GPQA, where the scores are 92.2% and 77.5%.
Qwen3 235B 2507 has the edge for knowledge tasks in this comparison, averaging 76.2 versus 58. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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