Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 1.7B
~39
0/8 categoriesNemotron Ultra 253B
41
Winner · 4/8 categories1-bit Bonsai 1.7B· Nemotron Ultra 253B
Pick Nemotron Ultra 253B if you want the stronger benchmark profile. 1-bit Bonsai 1.7B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Nemotron Ultra 253B has the cleaner overall profile here, landing at 41 versus 39. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Nemotron Ultra 253B's sharpest advantage is in knowledge, where it averages 42.6 against 20.7. The single biggest benchmark swing on the page is MATH-500, 34.4% to 74%.
Nemotron Ultra 253B is the reasoning model in the pair, while 1-bit Bonsai 1.7B 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.
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 Ultra 253B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 46% |
| BrowseComp | — | 50% |
| OSWorld-Verified | — | 45% |
| Coding | ||
| HumanEval | — | 41% |
| SWE-bench Verified | — | 31% |
| LiveCodeBench | — | 30% |
| SWE-bench Pro | — | 38% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 37% |
| OfficeQA Pro | — | 54% |
| ReasoningNemotron Ultra 253B wins | ||
| MuSR | 45.1% | 45% |
| BBH | — | 77% |
| LongBench v2 | — | 55% |
| MRCRv2 | — | 56% |
| KnowledgeNemotron Ultra 253B wins | ||
| GPQA | 20.7% | 48% |
| MMLU | — | 49% |
| SuperGPQA | — | 46% |
| MMLU-Pro | — | 63% |
| HLE | — | 11% |
| FrontierScience | — | 49% |
| SimpleQA | — | 47% |
| Instruction FollowingNemotron Ultra 253B wins | ||
| IFEval | 63% | 78% |
| Multilingual | ||
| MGSM | — | 74% |
| MMLU-ProX | — | 68% |
| MathematicsNemotron Ultra 253B wins | ||
| MATH-500 | 34.4% | 74% |
| AIME 2023 | — | 49% |
| AIME 2024 | — | 51% |
| AIME 2025 | — | 50% |
| HMMT Feb 2023 | — | 45% |
| HMMT Feb 2024 | — | 47% |
| HMMT Feb 2025 | — | 46% |
| BRUMO 2025 | — | 48% |
Nemotron Ultra 253B is ahead overall, 41 to 39. The biggest single separator in this matchup is MATH-500, where the scores are 34.4% and 74%.
Nemotron Ultra 253B has the edge for knowledge tasks in this comparison, averaging 42.6 versus 20.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Nemotron Ultra 253B has the edge for math in this comparison, averaging 55.3 versus 34.4. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
Nemotron Ultra 253B has the edge for reasoning in this comparison, averaging 52.7 versus 45.1. Inside this category, MuSR is the benchmark that creates the most daylight between them.
Nemotron Ultra 253B has the edge for instruction following in this comparison, averaging 78 versus 63. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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