Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
K-Exaone
~50
1/8 categoriesSarvam 105B
60
Winner · 0/8 categoriesK-Exaone· Sarvam 105B
Pick Sarvam 105B if you want the stronger benchmark profile. K-Exaone only becomes the better choice if coding is the priority or you need the larger 256K context window.
Sarvam 105B is clearly ahead on the aggregate, 60 to 50. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
K-Exaone 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 | K-Exaone | Sarvam 105B |
|---|---|---|
| Agentic | ||
| BrowseComp | — | 49.5% |
| CodingK-Exaone wins | ||
| SWE-bench Verified | 49.4% | 45% |
| LiveCodeBench v6 | — | 71.7% |
| 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% |
Sarvam 105B is ahead overall, 60 to 50. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 49.4% and 45%.
K-Exaone has the edge for coding in this comparison, averaging 49.4 versus 45. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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