Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Exaone 4.0 32B
63
Ling 2.6 Flash
36
Pick Exaone 4.0 32B if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you need the larger 262K context window or you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+22.8 difference
Exaone 4.0 32B
Ling 2.6 Flash
N/A
$null / $null
N/A
209.5 t/s
N/A
1.07s
128K
262K
Pick Exaone 4.0 32B if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you need the larger 262K context window or 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, 63 to 36. 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 59.
Exaone 4.0 32B is the reasoning model in the pair, while Ling 2.6 Flash 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. Ling 2.6 Flash gives you the larger context window at 262K, compared with 128K for Exaone 4.0 32B.
Exaone 4.0 32B is ahead on BenchLM's provisional leaderboard, 63 to 36.
Exaone 4.0 32B has the edge for knowledge tasks in this comparison, averaging 81.8 versus 59. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
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