Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E4B
~47
2/8 categoriesNemotron 3 Super 100B
56
Winner · 2/8 categoriesGemma 4 E4B· Nemotron 3 Super 100B
Pick Nemotron 3 Super 100B if you want the stronger benchmark profile. Gemma 4 E4B only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Nemotron 3 Super 100B is clearly ahead on the aggregate, 56 to 47. 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 reasoning, where it averages 71 against 25.4. The single biggest benchmark swing on the page is BBH, 33.1% to 83%. Gemma 4 E4B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 E4B is the reasoning model in the pair, while Nemotron 3 Super 100B 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. Nemotron 3 Super 100B gives you the larger context window at 1M, compared with 128K for Gemma 4 E4B.
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 | Gemma 4 E4B | Nemotron 3 Super 100B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 56% |
| BrowseComp | — | 61% |
| OSWorld-Verified | — | 54% |
| CodingGemma 4 E4B wins | ||
| LiveCodeBench | 52% | 38% |
| HumanEval | — | 57% |
| SWE-bench Verified | — | 44% |
| Multimodal & GroundedNemotron 3 Super 100B wins | ||
| MMMU-Pro | 52.6% | 55% |
| OfficeQA Pro | — | 67% |
| ReasoningNemotron 3 Super 100B wins | ||
| BBH | 33.1% | 83% |
| MRCRv2 | 25.4% | 75% |
| MuSR | — | 60% |
| LongBench v2 | — | 75% |
| KnowledgeGemma 4 E4B wins | ||
| GPQA | 58.6% | 64% |
| MMLU-Pro | 69.4% | 72% |
| MMLU | — | 65% |
| SuperGPQA | — | 62% |
| HLE | — | 13% |
| FrontierScience | — | 63% |
| SimpleQA | — | 62% |
| Instruction Following | ||
| IFEval | — | 84% |
| Multilingual | ||
| MGSM | — | 84% |
| MMLU-ProX | — | 77% |
| Mathematics | ||
| AIME 2023 | — | 65% |
| AIME 2024 | — | 67% |
| AIME 2025 | — | 66% |
| HMMT Feb 2023 | — | 61% |
| BRUMO 2025 | — | 64% |
| MATH-500 | — | 83% |
Nemotron 3 Super 100B is ahead overall, 56 to 47. The biggest single separator in this matchup is BBH, where the scores are 33.1% and 83%.
Gemma 4 E4B has the edge for knowledge tasks in this comparison, averaging 65.6 versus 53.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 E4B has the edge for coding in this comparison, averaging 52 versus 40.3. Inside this category, LiveCodeBench 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 25.4. Inside this category, BBH is the benchmark that creates the most daylight between them.
Nemotron 3 Super 100B has the edge for multimodal and grounded tasks in this comparison, averaging 60.4 versus 52.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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