Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 31B
65
Qwen3 235B 2507
33
Pick Gemma 4 31B if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+14.9 difference
Gemma 4 31B
Qwen3 235B 2507
$0 / $0
$0 / $0
N/A
N/A
N/A
N/A
256K
128K
Pick Gemma 4 31B if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Gemma 4 31B is clearly ahead on the provisional aggregate, 65 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 31B 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. Gemma 4 31B gives you the larger context window at 256K, compared with 128K for Qwen3 235B 2507.
Gemma 4 31B is ahead on BenchLM's provisional leaderboard, 65 to 33. The biggest single separator in this matchup is GPQA, where the scores are 84.3% and 77.5%.
Qwen3 235B 2507 has the edge for knowledge tasks in this comparison, averaging 76.2 versus 61.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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