Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E2B
~39
1/8 categoriesLlama 4 Scout
44
Winner · 2/8 categoriesGemma 4 E2B· Llama 4 Scout
Pick Llama 4 Scout if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Llama 4 Scout is clearly ahead on the aggregate, 44 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Llama 4 Scout's sharpest advantage is in reasoning, where it averages 43 against 19.1. The single biggest benchmark swing on the page is BBH, 21.9% to 60%. Gemma 4 E2B does hit back in knowledge, 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 Llama 4 Scout 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. Llama 4 Scout gives you the larger context window at 10M, compared with 128K for Gemma 4 E2B.
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 | Llama 4 Scout |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 39% |
| Coding | ||
| LiveCodeBench | 44% | — |
| HumanEval | — | 39% |
| Multimodal & GroundedLlama 4 Scout wins | ||
| MMMU-Pro | 44.2% | 60% |
| OfficeQA Pro | — | 55% |
| ReasoningLlama 4 Scout wins | ||
| BBH | 21.9% | 60% |
| MRCRv2 | 19.1% | — |
| MuSR | — | 43% |
| KnowledgeGemma 4 E2B wins | ||
| GPQA | 43.4% | — |
| MMLU-Pro | 60% | 51% |
| SuperGPQA | — | 44% |
| SimpleQA | — | 45% |
| Instruction Following | ||
| IFEval | — | 68% |
| Multilingual | ||
| MMLU-ProX | — | 58% |
| Mathematics | ||
| AIME 2025 | — | 48% |
| HMMT Feb 2023 | — | 43% |
| HMMT Feb 2024 | — | 45% |
| HMMT Feb 2025 | — | 44% |
| BRUMO 2025 | — | 46% |
Llama 4 Scout is ahead overall, 44 to 39. The biggest single separator in this matchup is BBH, where the scores are 21.9% and 60%.
Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 54.1 versus 47.6. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Llama 4 Scout has the edge for reasoning in this comparison, averaging 43 versus 19.1. Inside this category, BBH is the benchmark that creates the most daylight between them.
Llama 4 Scout has the edge for multimodal and grounded tasks in this comparison, averaging 57.8 versus 44.2. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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