Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
Winner · 1/8 categoriesSarvam 105B
60
1/8 categoriesGemma 4 31B· Sarvam 105B
Pick Gemma 4 31B if you want the stronger benchmark profile. Sarvam 105B only becomes the better choice if knowledge is the priority.
Gemma 4 31B is clearly ahead on the aggregate, 73 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 31B's sharpest advantage is in coding, where it averages 80 against 45. The single biggest benchmark swing on the page is MMLU-Pro, 85.2% to 81.7%. Sarvam 105B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 31B gives you the larger context window at 256K, compared with 128K for Sarvam 105B.
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 31B | Sarvam 105B |
|---|---|---|
| Agentic | ||
| BrowseComp | — | 49.5% |
| CodingGemma 4 31B wins | ||
| LiveCodeBench | 80% | — |
| LiveCodeBench v6 | — | 71.7% |
| SWE-bench Verified | — | 45% |
| Multimodal & Grounded | ||
| MMMU-Pro | 76.9% | — |
| Reasoning | ||
| BBH | 74.4% | — |
| MRCRv2 | 66.4% | — |
| gpqaDiamond | — | 78.7% |
| hle | — | 11.2% |
| KnowledgeSarvam 105B wins | ||
| GPQA | 84.3% | — |
| MMLU-Pro | 85.2% | 81.7% |
| HLE | 26.5% | — |
| HLE w/o tools | 19.5% | — |
| MMLU | — | 90.6% |
| Instruction Following | ||
| IFEval | — | 84.8% |
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| MATH-500 | — | 98.6% |
| AIME 2025 | — | 88.3% |
| HMMT Feb 2025 | — | 85.8% |
| HMMT Nov 2025 | — | 85.8% |
Gemma 4 31B is ahead overall, 73 to 60. The biggest single separator in this matchup is MMLU-Pro, where the scores are 85.2% and 81.7%.
Sarvam 105B has the edge for knowledge tasks in this comparison, averaging 81.7 versus 61.3. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for coding in this comparison, averaging 80 versus 45. Sarvam 105B stays close enough that the answer can still flip depending on your workload.
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