Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 1.7B
~39
0/8 categoriesNemotron-4 15B
40
Winner · 3/8 categories1-bit Bonsai 1.7B· Nemotron-4 15B
Pick Nemotron-4 15B if you want the stronger benchmark profile. 1-bit Bonsai 1.7B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Nemotron-4 15B finishes one point ahead overall, 40 to 39. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Nemotron-4 15B's sharpest advantage is in mathematics, where it averages 54.1 against 34.4. The single biggest benchmark swing on the page is GPQA, 20.7% to 53%.
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 1.7B | Nemotron-4 15B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 37% |
| BrowseComp | — | 47% |
| OSWorld-Verified | — | 42% |
| Coding | ||
| HumanEval | — | 46% |
| SWE-bench Verified | — | 31% |
| LiveCodeBench | — | 22% |
| SWE-bench Pro | — | 30% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 46% |
| OfficeQA Pro | — | 54% |
| ReasoningNemotron-4 15B wins | ||
| MuSR | 45.1% | 50% |
| BBH | — | 73% |
| LongBench v2 | — | 52% |
| MRCRv2 | — | 51% |
| KnowledgeNemotron-4 15B wins | ||
| GPQA | 20.7% | 53% |
| MMLU | — | 54% |
| SuperGPQA | — | 51% |
| HLE | — | 5% |
| FrontierScience | — | 50% |
| SimpleQA | — | 52% |
| Instruction Following | ||
| IFEval | 63% | — |
| Multilingual | ||
| MGSM | — | 75% |
| MMLU-ProX | — | 71% |
| MathematicsNemotron-4 15B wins | ||
| MATH-500 | 34.4% | — |
| AIME 2023 | — | 54% |
| AIME 2024 | — | 56% |
| AIME 2025 | — | 55% |
| HMMT Feb 2023 | — | 50% |
| HMMT Feb 2024 | — | 52% |
| HMMT Feb 2025 | — | 51% |
| BRUMO 2025 | — | 53% |
Nemotron-4 15B is ahead overall, 40 to 39. The biggest single separator in this matchup is GPQA, where the scores are 20.7% and 53%.
Nemotron-4 15B has the edge for knowledge tasks in this comparison, averaging 37.7 versus 20.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Nemotron-4 15B has the edge for math in this comparison, averaging 54.1 versus 34.4. 1-bit Bonsai 1.7B stays close enough that the answer can still flip depending on your workload.
Nemotron-4 15B has the edge for reasoning in this comparison, averaging 51.1 versus 45.1. Inside this category, MuSR is the benchmark that creates the most daylight between them.
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