Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Exaone 4.0 32B
65
Qwen3.5 397B
64
Verified leaderboard positions: Exaone 4.0 32B unranked · Qwen3.5 397B #15
Pick Exaone 4.0 32B if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+16.6 difference
Exaone 4.0 32B
Qwen3.5 397B
N/A
$0.6 / $3.6
N/A
96 t/s
N/A
2.44s
128K
128K
Pick Exaone 4.0 32B if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Exaone 4.0 32B finishes one point ahead on BenchLM's provisional leaderboard, 65 to 64. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Exaone 4.0 32B's sharpest advantage is in knowledge, where it averages 81.8 against 65.2. The single biggest benchmark swing on the page is MMLU-Pro, 81.8% to 87.8%.
Exaone 4.0 32B is the reasoning model in the pair, while Qwen3.5 397B 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 64. The biggest single separator in this matchup is MMLU-Pro, where the scores are 81.8% and 87.8%.
Exaone 4.0 32B has the edge for knowledge tasks in this comparison, averaging 81.8 versus 65.2. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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