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 48. 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 77.
Exaone 4.0 32B is the reasoning model in the pair, while DeepSeek LLM 2.0 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. DeepSeek LLM 2.0 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.
Benchmark data for this category is coming soon.
DeepSeek LLM 2.0
77
Exaone 4.0 32B
81.8
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 is ahead overall, 83 to 48.
Exaone 4.0 32B has the edge for knowledge tasks in this comparison, averaging 81.8 versus 77. DeepSeek LLM 2.0 stays close enough that the answer can still flip depending on your workload.
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