Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Exaone 4.0 32B is clearly ahead on the aggregate, 83 to 54. 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 mathematics, where it averages 85.3 against 84.
Exaone 4.0 32B is the reasoning model in the pair, while Qwen2.5-72B 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.
Pick Exaone 4.0 32B if you want the stronger benchmark profile. Qwen2.5-72B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Benchmark data for this category is coming soon.
Benchmark data for this category is coming soon.
Benchmark data for this category is coming soon.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Exaone 4.0 32B
81.8
Qwen2.5-72B
80.6
Benchmark data for this category is coming soon.
Benchmark data for this category is coming soon.
Exaone 4.0 32B
85.3
Qwen2.5-72B
84
Exaone 4.0 32B is ahead overall, 83 to 54.
Exaone 4.0 32B has the edge for knowledge tasks in this comparison, averaging 81.8 versus 80.6. Qwen2.5-72B stays close enough that the answer can still flip depending on your workload.
Exaone 4.0 32B has the edge for math in this comparison, averaging 85.3 versus 84. Qwen2.5-72B stays close enough that the answer can still flip depending on your workload.
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