Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Exaone 4.0 32B
65
Qwen3 235B 2507
33
Pick Exaone 4.0 32B if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+5.6 difference
Exaone 4.0 32B
Qwen3 235B 2507
N/A
$0 / $0
N/A
N/A
N/A
N/A
128K
128K
Pick Exaone 4.0 32B if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Exaone 4.0 32B 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.
Exaone 4.0 32B's sharpest advantage is in knowledge, where it averages 81.8 against 76.2. The single biggest benchmark swing on the page is MMLU-Pro, 81.8% to 83%.
Exaone 4.0 32B 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.
Exaone 4.0 32B is ahead on BenchLM's provisional leaderboard, 65 to 33. The biggest single separator in this matchup is MMLU-Pro, where the scores are 81.8% and 83%.
Exaone 4.0 32B has the edge for knowledge tasks in this comparison, averaging 81.8 versus 76.2. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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