Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 8B
~50
0/8 categoriesNemotron 3 Super 100B
57
Winner · 4/8 categories1-bit Bonsai 8B· Nemotron 3 Super 100B
Pick Nemotron 3 Super 100B if you want the stronger benchmark profile. 1-bit Bonsai 8B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Nemotron 3 Super 100B is clearly ahead on the aggregate, 57 to 50. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Nemotron 3 Super 100B's sharpest advantage is in knowledge, where it averages 53.4 against 30. The single biggest benchmark swing on the page is GPQA, 30% to 64%.
Nemotron 3 Super 100B gives you the larger context window at 1M, compared with 64K for 1-bit Bonsai 8B.
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 8B | Nemotron 3 Super 100B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 56% |
| BrowseComp | — | 61% |
| OSWorld-Verified | — | 54% |
| Coding | ||
| HumanEval | — | 57% |
| SWE-bench Verified | — | 44% |
| LiveCodeBench | — | 38% |
| SWE-bench Pro | — | 44% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 55% |
| OfficeQA Pro | — | 67% |
| ReasoningNemotron 3 Super 100B wins | ||
| MuSR | 50% | 60% |
| BBH | — | 83% |
| LongBench v2 | — | 75% |
| MRCRv2 | — | 75% |
| KnowledgeNemotron 3 Super 100B wins | ||
| GPQA | 30% | 64% |
| MMLU | — | 65% |
| SuperGPQA | — | 62% |
| MMLU-Pro | — | 72% |
| HLE | — | 13% |
| FrontierScience | — | 63% |
| SimpleQA | — | 62% |
| Instruction FollowingNemotron 3 Super 100B wins | ||
| IFEval | 79.8% | 84% |
| Multilingual | ||
| MGSM | — | 84% |
| MMLU-ProX | — | 77% |
| MathematicsNemotron 3 Super 100B wins | ||
| MATH-500 | 66% | 83% |
| AIME 2023 | — | 65% |
| AIME 2024 | — | 67% |
| AIME 2025 | — | 66% |
| HMMT Feb 2023 | — | 61% |
| HMMT Feb 2024 | — | 63% |
| HMMT Feb 2025 | — | 62% |
| BRUMO 2025 | — | 64% |
Nemotron 3 Super 100B is ahead overall, 57 to 50. The biggest single separator in this matchup is GPQA, where the scores are 30% and 64%.
Nemotron 3 Super 100B has the edge for knowledge tasks in this comparison, averaging 53.4 versus 30. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Nemotron 3 Super 100B has the edge for math in this comparison, averaging 69.6 versus 66. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
Nemotron 3 Super 100B has the edge for reasoning in this comparison, averaging 71 versus 50. Inside this category, MuSR is the benchmark that creates the most daylight between them.
Nemotron 3 Super 100B has the edge for instruction following in this comparison, averaging 84 versus 79.8. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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