Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Claude 3 Haiku
43
Winner · 2/8 categoriesGemma 4 E2B
~39
2/8 categoriesClaude 3 Haiku· Gemma 4 E2B
Pick Claude 3 Haiku if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if coding is the priority or you want the stronger reasoning-first profile.
Claude 3 Haiku is clearly ahead on the aggregate, 43 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude 3 Haiku's sharpest advantage is in reasoning, where it averages 60.1 against 19.1. The single biggest benchmark swing on the page is BBH, 74% to 21.9%. 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 Claude 3 Haiku 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. Claude 3 Haiku gives you the larger context window at 200K, 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 | Claude 3 Haiku | Gemma 4 E2B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 40% | — |
| BrowseComp | 53% | — |
| OSWorld-Verified | 42% | — |
| CodingGemma 4 E2B wins | ||
| HumanEval | 73% | — |
| SWE-bench Verified | 17% | — |
| LiveCodeBench | 20% | 44% |
| SWE-bench Pro | 19% | — |
| Multimodal & GroundedClaude 3 Haiku wins | ||
| MMMU-Pro | 70% | 44.2% |
| OfficeQA Pro | 67% | — |
| ReasoningClaude 3 Haiku wins | ||
| MuSR | 52% | — |
| BBH | 74% | 21.9% |
| LongBench v2 | 63% | — |
| MRCRv2 | 63% | 19.1% |
| KnowledgeGemma 4 E2B wins | ||
| MMLU | 75.2% | — |
| GPQA | 56% | 43.4% |
| SuperGPQA | 54% | — |
| MMLU-Pro | 63% | 60% |
| HLE | 2% | — |
| FrontierScience | 50% | — |
| SimpleQA | 54% | — |
| Instruction Following | ||
| IFEval | 76% | — |
| Multilingual | ||
| MGSM | 73% | — |
| MMLU-ProX | 70% | — |
| Mathematics | ||
| AIME 2023 | 56% | — |
| AIME 2024 | 58% | — |
| AIME 2025 | 57% | — |
| HMMT Feb 2023 | 52% | — |
| HMMT Feb 2024 | 54% | — |
| HMMT Feb 2025 | 53% | — |
| BRUMO 2025 | 55% | — |
| MATH-500 | 71% | — |
Claude 3 Haiku is ahead overall, 43 to 39. The biggest single separator in this matchup is BBH, where the scores are 74% and 21.9%.
Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 54.1 versus 43.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 E2B has the edge for coding in this comparison, averaging 44 versus 18.9. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Claude 3 Haiku has the edge for reasoning in this comparison, averaging 60.1 versus 19.1. Inside this category, BBH is the benchmark that creates the most daylight between them.
Claude 3 Haiku has the edge for multimodal and grounded tasks in this comparison, averaging 68.7 versus 44.2. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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