Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mixtral 8x22B Instruct v0.1
36
0/8 categoriesSarvam 105B
60
Winner · 3/8 categoriesMixtral 8x22B Instruct v0.1· Sarvam 105B
Pick Sarvam 105B if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Sarvam 105B is clearly ahead on the aggregate, 60 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Sarvam 105B's sharpest advantage is in knowledge, where it averages 81.7 against 53. The single biggest benchmark swing on the page is BrowseComp, 32% to 49.5%.
Sarvam 105B is the reasoning model in the pair, while Mixtral 8x22B Instruct v0.1 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 Mixtral 8x22B Instruct v0.1.
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 | Mixtral 8x22B Instruct v0.1 | Sarvam 105B |
|---|---|---|
| AgenticSarvam 105B wins | ||
| Terminal-Bench 2.0 | 35% | — |
| BrowseComp | 32% | 49.5% |
| OSWorld-Verified | 28% | — |
| CodingSarvam 105B wins | ||
| HumanEval | 54.8% | — |
| SWE-bench Pro | 40% | — |
| LiveCodeBench v6 | — | 71.7% |
| SWE-bench Verified | — | 45% |
| Multimodal & Grounded | ||
| MMMU-Pro | 35% | — |
| OfficeQA Pro | 36% | — |
| Reasoning | ||
| LongBench v2 | 39% | — |
| MRCRv2 | 38% | — |
| gpqaDiamond | — | 78.7% |
| hle | — | 11.2% |
| KnowledgeSarvam 105B wins | ||
| MMLU | 77.8% | 90.6% |
| FrontierScience | 53% | — |
| MMLU-Pro | — | 81.7% |
| Instruction Following | ||
| IFEval | — | 84.8% |
| Multilingual | ||
| MMLU-ProX | 42% | — |
| Mathematics | ||
| MATH-500 | — | 98.6% |
| AIME 2025 | — | 88.3% |
| HMMT Feb 2025 | — | 85.8% |
| HMMT Nov 2025 | — | 85.8% |
Sarvam 105B is ahead overall, 60 to 36. The biggest single separator in this matchup is BrowseComp, where the scores are 32% and 49.5%.
Sarvam 105B has the edge for knowledge tasks in this comparison, averaging 81.7 versus 53. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Sarvam 105B has the edge for coding in this comparison, averaging 45 versus 40. Mixtral 8x22B Instruct v0.1 stays close enough that the answer can still flip depending on your workload.
Sarvam 105B has the edge for agentic tasks in this comparison, averaging 49.5 versus 31.8. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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