Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 3 Pro
79
Winner · 4/8 categoriesSarvam 30B
48
0/8 categoriesGemini 3 Pro· Sarvam 30B
Pick Gemini 3 Pro if you want the stronger benchmark profile. Sarvam 30B only becomes the better choice if you want the stronger reasoning-first profile.
Gemini 3 Pro is clearly ahead on the aggregate, 79 to 48. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3 Pro's sharpest advantage is in agentic, where it averages 71.1 against 35.5. The single biggest benchmark swing on the page is BrowseComp, 83% to 35.5%.
Sarvam 30B is the reasoning model in the pair, while Gemini 3 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. Gemini 3 Pro gives you the larger context window at 2M, compared with 64K for Sarvam 30B.
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 | Sarvam 30B |
|---|---|---|
| AgenticGemini 3 Pro wins | ||
| Terminal-Bench 2.0 | 68% | — |
| BrowseComp | 83% | 35.5% |
| OSWorld-Verified | 66% | — |
| CodingGemini 3 Pro wins | ||
| HumanEval | 91% | 92.1% |
| SWE-bench Verified | 59% | 34% |
| LiveCodeBench | 49% | — |
| SWE-bench Pro | 58% | — |
| LiveCodeBench v6 | — | 70.0% |
| Multimodal & Grounded | ||
| MMMU | 87.2% | — |
| MMMU-Pro | 81% | — |
| OfficeQA Pro | 92% | — |
| RealWorldQA | 83.3% | — |
| OmniDocBench 1.5 | 88.5% | — |
| MathVision | 86.6% | — |
| We-Math | 86.9% | — |
| DynaMath | 85.1% | — |
| MStar | 83.1% | — |
| SimpleVQA | 73.2% | — |
| ChatCVQA | 81.4% | — |
| MMLongBench-Doc | 60.5% | — |
| CC-OCR | 79.0% | — |
| AI2D_TEST | 94.1% | — |
| CountBench | 97.3% | — |
| RefCOCO (avg) | 84.1% | — |
| ODINW13 | 46.3% | — |
| ERQA | 70.5% | — |
| VideoMMMU | 87.6% | — |
| MLVU (M-Avg) | 83.0% | — |
| ScreenSpot Pro | 72.7% | — |
| Reasoning | ||
| MuSR | 93% | — |
| BBH | 90% | — |
| LongBench v2 | 90% | — |
| MRCRv2 | 87% | — |
| ARC-AGI-2 | 31.1% | — |
| gpqaDiamond | — | 66.5% |
| KnowledgeGemini 3 Pro wins | ||
| MMLU | 99% | 85.1% |
| GPQA | 97% | — |
| SuperGPQA | 95% | — |
| FrontierScience | 86% | — |
| SimpleQA | 95% | — |
| MMLU-Pro | — | 80% |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| Coming soon | ||
| MathematicsGemini 3 Pro wins | ||
| AIME 2023 | 99% | — |
| AIME 2024 | 99% | — |
| AIME 2025 | 98% | 80% |
| HMMT Feb 2023 | 95% | — |
| HMMT Feb 2024 | 97% | — |
| HMMT Feb 2025 | 96% | — |
| BRUMO 2025 | 96% | — |
| MATH-500 | — | 97% |
| HMMT Feb 2025 | — | 73.3% |
| HMMT Nov 2025 | — | 74.2% |
Gemini 3 Pro is ahead overall, 79 to 48. The biggest single separator in this matchup is BrowseComp, where the scores are 83% and 35.5%.
Gemini 3 Pro has the edge for knowledge tasks in this comparison, averaging 92.5 versus 80. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Gemini 3 Pro has the edge for coding in this comparison, averaging 54.8 versus 34. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Gemini 3 Pro has the edge for math in this comparison, averaging 97.1 versus 86.5. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
Gemini 3 Pro has the edge for agentic tasks in this comparison, averaging 71.1 versus 35.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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