Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen3.5-35B-A3B
66
Winner · 3/8 categoriesSarvam 105B
60
1/8 categoriesQwen3.5-35B-A3B· Sarvam 105B
Pick Qwen3.5-35B-A3B if you want the stronger benchmark profile. Sarvam 105B only becomes the better choice if knowledge is the priority.
Qwen3.5-35B-A3B is clearly ahead on the aggregate, 66 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5-35B-A3B's sharpest advantage is in coding, where it averages 72.6 against 45. The single biggest benchmark swing on the page is SWE-bench Verified, 69.2% to 45%. Sarvam 105B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Qwen3.5-35B-A3B gives you the larger context window at 262K, 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 | Qwen3.5-35B-A3B | Sarvam 105B |
|---|---|---|
| AgenticQwen3.5-35B-A3B wins | ||
| Terminal-Bench 2.0 | 40.5% | — |
| BrowseComp | 61% | 49.5% |
| OSWorld-Verified | 54.5% | — |
| Tau2-Telecom | 81.2% | — |
| CodingQwen3.5-35B-A3B wins | ||
| SWE-bench Verified | 69.2% | 45% |
| LiveCodeBench | 74.6% | — |
| LiveCodeBench v6 | — | 71.7% |
| Multimodal & Grounded | ||
| MMMU-Pro | 75.1% | — |
| Reasoning | ||
| LongBench v2 | 59% | — |
| gpqaDiamond | — | 78.7% |
| hle | — | 11.2% |
| KnowledgeSarvam 105B wins | ||
| MMLU-Pro | 85.3% | 81.7% |
| SuperGPQA | 63.4% | — |
| GPQA | 84.2% | — |
| MMLU | — | 90.6% |
| Instruction FollowingQwen3.5-35B-A3B wins | ||
| IFEval | 91.9% | 84.8% |
| Multilingual | ||
| MMLU-ProX | 81% | — |
| Mathematics | ||
| MATH-500 | — | 98.6% |
| AIME 2025 | — | 88.3% |
| HMMT Feb 2025 | — | 85.8% |
| HMMT Nov 2025 | — | 85.8% |
Qwen3.5-35B-A3B is ahead overall, 66 to 60. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 69.2% and 45%.
Sarvam 105B has the edge for knowledge tasks in this comparison, averaging 81.7 versus 79.3. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for coding in this comparison, averaging 72.6 versus 45. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for agentic tasks in this comparison, averaging 50.5 versus 49.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for instruction following in this comparison, averaging 91.9 versus 84.8. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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