Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 3 Pro Deep Think
80
Winner · 4/8 categoriesGemma 4 E2B
~39
0/8 categoriesGemini 3 Pro Deep Think· Gemma 4 E2B
Pick Gemini 3 Pro Deep Think if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Gemini 3 Pro Deep Think is clearly ahead on the aggregate, 80 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3 Pro Deep Think's sharpest advantage is in reasoning, where it averages 82.1 against 19.1. The single biggest benchmark swing on the page is MRCRv2, 96% to 19.1%.
Gemini 3 Pro Deep Think gives you the larger context window at 2M, 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 | Gemini 3 Pro Deep Think | Gemma 4 E2B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 77% | — |
| BrowseComp | 87% | — |
| OSWorld-Verified | 73% | — |
| CodingGemini 3 Pro Deep Think wins | ||
| HumanEval | 91% | — |
| SWE-bench Verified | 58% | — |
| LiveCodeBench | 58% | 44% |
| Multimodal & GroundedGemini 3 Pro Deep Think wins | ||
| MMMU-Pro | 95% | 44.2% |
| OfficeQA Pro | 95% | — |
| ReasoningGemini 3 Pro Deep Think wins | ||
| MuSR | 93% | — |
| BBH | 95% | 21.9% |
| LongBench v2 | 94% | — |
| MRCRv2 | 96% | 19.1% |
| ARC-AGI-2 | 45.1% | — |
| KnowledgeGemini 3 Pro Deep Think wins | ||
| MMLU | 99% | — |
| GPQA | 97% | 43.4% |
| SuperGPQA | 95% | — |
| MMLU-Pro | 81% | 60% |
| HLE | 32% | — |
| FrontierScience | 88% | — |
| SimpleQA | 95% | — |
| Instruction Following | ||
| IFEval | 89% | — |
| Multilingual | ||
| MGSM | 92% | — |
| MMLU-ProX | 85% | — |
| Mathematics | ||
| AIME 2023 | 99% | — |
| AIME 2024 | 99% | — |
| HMMT Feb 2024 | 97% | — |
| HMMT Feb 2025 | 96% | — |
| BRUMO 2025 | 96% | — |
| MATH-500 | 92% | — |
Gemini 3 Pro Deep Think is ahead overall, 80 to 39. The biggest single separator in this matchup is MRCRv2, where the scores are 96% and 19.1%.
Gemini 3 Pro Deep Think has the edge for knowledge tasks in this comparison, averaging 76.4 versus 54.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemini 3 Pro Deep Think has the edge for coding in this comparison, averaging 58 versus 44. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Gemini 3 Pro Deep Think has the edge for reasoning in this comparison, averaging 82.1 versus 19.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Gemini 3 Pro Deep Think has the edge for multimodal and grounded tasks in this comparison, averaging 95 versus 44.2. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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