Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 4B
~44
Winner · 1/8 categoriesGemma 4 E2B
~39
1/8 categories1-bit Bonsai 4B· Gemma 4 E2B
Pick 1-bit Bonsai 4B if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if knowledge is the priority or you need the larger 128K context window.
1-bit Bonsai 4B is clearly ahead on the aggregate, 44 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
1-bit Bonsai 4B's sharpest advantage is in reasoning, where it averages 41.4 against 19.1. The single biggest benchmark swing on the page is GPQA, 28.7% to 43.4%. Gemma 4 E2B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 E2B 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. Gemma 4 E2B 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 | Gemma 4 E2B |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| LiveCodeBench | — | 44% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 44.2% |
| Reasoning1-bit Bonsai 4B wins | ||
| MuSR | 41.4% | — |
| BBH | — | 21.9% |
| MRCRv2 | — | 19.1% |
| KnowledgeGemma 4 E2B wins | ||
| GPQA | 28.7% | 43.4% |
| MMLU-Pro | — | 60% |
| Instruction Following | ||
| IFEval | 69.6% | — |
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| MATH-500 | 65.8% | — |
1-bit Bonsai 4B is ahead overall, 44 to 39. The biggest single separator in this matchup is GPQA, where the scores are 28.7% and 43.4%.
Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 54.1 versus 28.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
1-bit Bonsai 4B has the edge for reasoning in this comparison, averaging 41.4 versus 19.1. Gemma 4 E2B stays close enough that the answer can still flip depending on your workload.
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