Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 4B
~44
0/8 categoriesExaone 4.0 32B
~75
Winner · 2/8 categories1-bit Bonsai 4B· Exaone 4.0 32B
Pick Exaone 4.0 32B if you want the stronger benchmark profile. 1-bit Bonsai 4B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Exaone 4.0 32B is clearly ahead on the aggregate, 75 to 44. 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 28.7.
Exaone 4.0 32B is the reasoning model in the pair, while 1-bit Bonsai 4B 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 gives you the larger context window at 128K, compared with 32K for 1-bit Bonsai 4B.
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 | 1-bit Bonsai 4B | Exaone 4.0 32B |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| Coming soon | ||
| Multimodal & Grounded | ||
| Coming soon | ||
| Reasoning | ||
| MuSR | 41.4% | — |
| KnowledgeExaone 4.0 32B wins | ||
| GPQA | 28.7% | — |
| MMLU-Pro | — | 81.8% |
| Instruction Following | ||
| IFEval | 69.6% | — |
| Multilingual | ||
| Coming soon | ||
| MathematicsExaone 4.0 32B wins | ||
| MATH-500 | 65.8% | — |
| AIME 2025 | — | 85.3% |
Exaone 4.0 32B is ahead overall, 75 to 44.
Exaone 4.0 32B has the edge for knowledge tasks in this comparison, averaging 81.8 versus 28.7. 1-bit Bonsai 4B 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 65.8. 1-bit Bonsai 4B stays close enough that the answer can still flip depending on your workload.
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