Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E2B
~39
2/8 categoriesNemotron-4 15B
42
Winner · 2/8 categoriesGemma 4 E2B· Nemotron-4 15B
Pick Nemotron-4 15B if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if coding is the priority or you need the larger 128K context window.
Nemotron-4 15B has the cleaner overall profile here, landing at 42 versus 39. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Nemotron-4 15B's sharpest advantage is in reasoning, where it averages 51.1 against 19.1. The single biggest benchmark swing on the page is BBH, 21.9% to 73%. Gemma 4 E2B does hit back in coding, 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 Nemotron-4 15B 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 Nemotron-4 15B.
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 E2B | Nemotron-4 15B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 37% |
| BrowseComp | — | 47% |
| OSWorld-Verified | — | 42% |
| CodingGemma 4 E2B wins | ||
| LiveCodeBench | 44% | 22% |
| HumanEval | — | 46% |
| SWE-bench Verified | — | 31% |
| Multimodal & GroundedNemotron-4 15B wins | ||
| MMMU-Pro | 44.2% | 46% |
| OfficeQA Pro | — | 54% |
| ReasoningNemotron-4 15B wins | ||
| BBH | 21.9% | 73% |
| MRCRv2 | 19.1% | 51% |
| MuSR | — | 50% |
| LongBench v2 | — | 52% |
| KnowledgeGemma 4 E2B wins | ||
| GPQA | 43.4% | — |
| MMLU-Pro | 60% | 63% |
| MMLU | — | 54% |
| HLE | — | 5% |
| FrontierScience | — | 50% |
| Instruction Following | ||
| IFEval | — | 79% |
| Multilingual | ||
| MGSM | — | 75% |
| MMLU-ProX | — | 71% |
| Mathematics | ||
| AIME 2023 | — | 54% |
| AIME 2024 | — | 56% |
| HMMT Feb 2025 | — | 51% |
| BRUMO 2025 | — | 53% |
| MATH-500 | — | 71% |
Nemotron-4 15B is ahead overall, 42 to 39. The biggest single separator in this matchup is BBH, where the scores are 21.9% and 73%.
Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 54.1 versus 38.1. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Gemma 4 E2B has the edge for coding in this comparison, averaging 44 versus 25.4. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Nemotron-4 15B has the edge for reasoning in this comparison, averaging 51.1 versus 19.1. Inside this category, BBH is the benchmark that creates the most daylight between them.
Nemotron-4 15B has the edge for multimodal and grounded tasks in this comparison, averaging 49.6 versus 44.2. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.