Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 1.0 Pro
40
Winner · 2/8 categoriesGemma 4 E2B
~39
2/8 categoriesGemini 1.0 Pro· Gemma 4 E2B
Pick Gemini 1.0 Pro 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.
Gemini 1.0 Pro finishes one point ahead overall, 40 to 39. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Gemini 1.0 Pro's sharpest advantage is in reasoning, where it averages 53.9 against 19.1. The single biggest benchmark swing on the page is BBH, 73% 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 Gemini 1.0 Pro 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 Gemini 1.0 Pro.
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 | Gemini 1.0 Pro | Gemma 4 E2B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 36% | — |
| BrowseComp | 51% | — |
| OSWorld-Verified | 36% | — |
| CodingGemma 4 E2B wins | ||
| HumanEval | 54% | — |
| SWE-bench Verified | 5% | — |
| LiveCodeBench | — | 44% |
| Multimodal & GroundedGemini 1.0 Pro wins | ||
| MMMU-Pro | 73% | 44.2% |
| OfficeQA Pro | 62% | — |
| ReasoningGemini 1.0 Pro wins | ||
| MuSR | 58% | — |
| BBH | 73% | 21.9% |
| LongBench v2 | 51% | — |
| MRCRv2 | 54% | 19.1% |
| KnowledgeGemma 4 E2B wins | ||
| MMLU | 62% | — |
| GPQA | 62% | 43.4% |
| SuperGPQA | 60% | — |
| MMLU-Pro | 54% | 60% |
| HLE | 1% | — |
| FrontierScience | 54% | — |
| SimpleQA | 60% | — |
| Instruction Following | ||
| IFEval | 77% | — |
| Multilingual | ||
| MGSM | 72% | — |
| MMLU-ProX | 64% | — |
| Mathematics | ||
| AIME 2023 | 62% | — |
| HMMT Feb 2023 | 58% | — |
| HMMT Feb 2024 | 60% | — |
| HMMT Feb 2025 | 59% | — |
| BRUMO 2025 | 61% | — |
| MATH-500 | 72% | — |
Gemini 1.0 Pro is ahead overall, 40 to 39. The biggest single separator in this matchup is BBH, where the scores are 73% and 21.9%.
Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 54.1 versus 44.3. 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 5. Gemini 1.0 Pro stays close enough that the answer can still flip depending on your workload.
Gemini 1.0 Pro has the edge for reasoning in this comparison, averaging 53.9 versus 19.1. Inside this category, BBH is the benchmark that creates the most daylight between them.
Gemini 1.0 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 68.1 versus 44.2. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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