Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Exaone 4.0 32B
~76
Winner · 1/8 categoriesGemma 4 31B
73
0/8 categoriesExaone 4.0 32B· Gemma 4 31B
Pick Exaone 4.0 32B if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if you need the larger 256K context window.
Exaone 4.0 32B has the cleaner overall profile here, landing at 76 versus 73. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Exaone 4.0 32B's sharpest advantage is in knowledge, where it averages 81.8 against 61.3. The single biggest benchmark swing on the page is MMLU-Pro, 81.8% to 85.2%.
Gemma 4 31B gives you the larger context window at 256K, compared with 128K for Exaone 4.0 32B.
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | Exaone 4.0 32B | Gemma 4 31B |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| LiveCodeBench | — | 80% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 76.9% |
| Reasoning | ||
| BBH | — | 74.4% |
| MRCRv2 | — | 66.4% |
| KnowledgeExaone 4.0 32B wins | ||
| MMLU-Pro | 81.8% | 85.2% |
| GPQA | — | 84.3% |
| HLE | — | 26.5% |
| HLE w/o tools | — | 19.5% |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| AIME 2025 | 85.3% | — |
Exaone 4.0 32B is ahead overall, 76 to 73. The biggest single separator in this matchup is MMLU-Pro, where the scores are 81.8% and 85.2%.
Exaone 4.0 32B has the edge for knowledge tasks in this comparison, averaging 81.8 versus 61.3. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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