Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 26B A4B
64
Winner · 1/8 categoriesSarvam 30B
48
1/8 categoriesGemma 4 26B A4B· Sarvam 30B
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. Sarvam 30B only becomes the better choice if knowledge is the priority.
Gemma 4 26B A4B is clearly ahead on the aggregate, 64 to 48. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 26B A4B's sharpest advantage is in coding, where it averages 77.1 against 34. The single biggest benchmark swing on the page is MMLU-Pro, 82.6% to 80%. Sarvam 30B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 26B A4B gives you the larger context window at 256K, 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 | Gemma 4 26B A4B | Sarvam 30B |
|---|---|---|
| Agentic | ||
| BrowseComp | — | 35.5% |
| CodingGemma 4 26B A4B wins | ||
| LiveCodeBench | 77.1% | — |
| HumanEval | — | 92.1% |
| LiveCodeBench v6 | — | 70.0% |
| SWE-bench Verified | — | 34% |
| Multimodal & Grounded | ||
| MMMU-Pro | 73.8% | — |
| Reasoning | ||
| BBH | 64.8% | — |
| MRCRv2 | 44.1% | — |
| gpqaDiamond | — | 66.5% |
| KnowledgeSarvam 30B wins | ||
| GPQA | 82.3% | — |
| MMLU-Pro | 82.6% | 80% |
| HLE | 17.2% | — |
| HLE w/o tools | 8.7% | — |
| MMLU | — | 85.1% |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| MATH-500 | — | 97% |
| AIME 2025 | — | 80% |
| HMMT Feb 2025 | — | 73.3% |
| HMMT Nov 2025 | — | 74.2% |
Gemma 4 26B A4B is ahead overall, 64 to 48. The biggest single separator in this matchup is MMLU-Pro, where the scores are 82.6% and 80%.
Sarvam 30B has the edge for knowledge tasks in this comparison, averaging 80 versus 56.1. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Gemma 4 26B A4B has the edge for coding in this comparison, averaging 77.1 versus 34. Sarvam 30B stays close enough that the answer can still flip depending on your workload.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.