Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Holo3-35B-A3B
~69
Winner · 1/8 categoriesSarvam 105B
60
0/8 categoriesHolo3-35B-A3B· Sarvam 105B
Pick Holo3-35B-A3B if you want the stronger benchmark profile. Sarvam 105B only becomes the better choice if you want the cheaper token bill or you need the larger 128K context window.
Holo3-35B-A3B is clearly ahead on the aggregate, 69 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Holo3-35B-A3B's sharpest advantage is in agentic, where it averages 77.8 against 49.5.
Holo3-35B-A3B is also the more expensive model on tokens at $0.25 input / $1.80 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Sarvam 105B. That is roughly Infinityx on output cost alone. Sarvam 105B is the reasoning model in the pair, while Holo3-35B-A3B 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. Sarvam 105B gives you the larger context window at 128K, compared with 64K for Holo3-35B-A3B.
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 | Holo3-35B-A3B | Sarvam 105B |
|---|---|---|
| AgenticHolo3-35B-A3B wins | ||
| OSWorld-Verified | 77.8% | — |
| BrowseComp | — | 49.5% |
| Coding | ||
| LiveCodeBench v6 | — | 71.7% |
| SWE-bench Verified | — | 45% |
| Multimodal & Grounded | ||
| Coming soon | ||
| Reasoning | ||
| gpqaDiamond | — | 78.7% |
| hle | — | 11.2% |
| Knowledge | ||
| MMLU | — | 90.6% |
| MMLU-Pro | — | 81.7% |
| 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% |
Holo3-35B-A3B is ahead overall, 69 to 60.
Holo3-35B-A3B has the edge for agentic tasks in this comparison, averaging 77.8 versus 49.5. Sarvam 105B 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.