Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Holo3-35B-A3B
~78
Winner · 1/8 categoriesKimi K2.5
71
0/8 categoriesHolo3-35B-A3B· Kimi K2.5
Pick Holo3-35B-A3B if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if you need the larger 128K context window.
Holo3-35B-A3B is clearly ahead on the aggregate, 78 to 71. 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 57.6. The single biggest benchmark swing on the page is OSWorld-Verified, 77.8% to 63.3%.
Kimi K2.5 is also the more expensive model on tokens at $0.50 input / $2.80 output per 1M tokens, versus $0.25 input / $1.80 output per 1M tokens for Holo3-35B-A3B. Kimi K2.5 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 | Kimi K2.5 |
|---|---|---|
| AgenticHolo3-35B-A3B wins | ||
| OSWorld-Verified | 77.8% | 63.3% |
| Terminal-Bench 2.0 | — | 50.8% |
| BrowseComp | — | 60.6% |
| Coding | ||
| HumanEval | — | 99% |
| SWE-bench Verified | — | 76.8% |
| LiveCodeBench | — | 85% |
| SWE-bench Pro | — | 40% |
| SWE-Rebench | — | 58.5% |
| React Native Evals | — | 74.9% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 78.5% |
| OfficeQA Pro | — | 69% |
| Reasoning | ||
| MuSR | — | 72% |
| BBH | — | 81% |
| LongBench v2 | — | 67% |
| MRCRv2 | — | 70% |
| Knowledge | ||
| MMLU | — | 77% |
| GPQA | — | 87.6% |
| SuperGPQA | — | 74% |
| MMLU-Pro | — | 87.1% |
| HLE | — | 11% |
| FrontierScience | — | 67% |
| SimpleQA | — | 74% |
| Instruction Following | ||
| IFEval | — | 94% |
| Multilingual | ||
| MGSM | — | 83% |
| MMLU-ProX | — | 78% |
| Mathematics | ||
| AIME 2023 | — | 77% |
| AIME 2024 | — | 79% |
| AIME 2025 | — | 78% |
| HMMT Feb 2023 | — | 73% |
| HMMT Feb 2024 | — | 75% |
| HMMT Feb 2025 | — | 74% |
| BRUMO 2025 | — | 76% |
| MATH-500 | — | 82% |
Holo3-35B-A3B is ahead overall, 78 to 71. The biggest single separator in this matchup is OSWorld-Verified, where the scores are 77.8% and 63.3%.
Holo3-35B-A3B has the edge for agentic tasks in this comparison, averaging 77.8 versus 57.6. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
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