Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek V3.2
62
0/8 categoriesHolo3-35B-A3B
~78
Winner · 1/8 categoriesDeepSeek V3.2· Holo3-35B-A3B
Pick Holo3-35B-A3B if you want the stronger benchmark profile. DeepSeek V3.2 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, 78 to 62. 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 58.8. The single biggest benchmark swing on the page is OSWorld-Verified, 55% to 77.8%.
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 DeepSeek V3.2. That is roughly Infinityx on output cost alone. DeepSeek V3.2 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 | DeepSeek V3.2 | Holo3-35B-A3B |
|---|---|---|
| AgenticHolo3-35B-A3B wins | ||
| Terminal-Bench 2.0 | 60% | — |
| BrowseComp | 62% | — |
| OSWorld-Verified | 55% | 77.8% |
| Coding | ||
| HumanEval | 76% | — |
| SWE-bench Verified | 45% | — |
| LiveCodeBench | 39% | — |
| SWE-bench Pro | 47% | — |
| SWE-Rebench | 60.9% | — |
| React Native Evals | 69% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 61% | — |
| OfficeQA Pro | 72% | — |
| Reasoning | ||
| MuSR | 79% | — |
| BBH | 81% | — |
| LongBench v2 | 69% | — |
| MRCRv2 | 70% | — |
| ARC-AGI-2 | 4% | — |
| Knowledge | ||
| MMLU | 84% | — |
| GPQA | 83% | — |
| SuperGPQA | 81% | — |
| MMLU-Pro | 73% | — |
| HLE | 11% | — |
| FrontierScience | 72% | — |
| SimpleQA | 81% | — |
| Instruction Following | ||
| IFEval | 85% | — |
| Multilingual | ||
| MGSM | 84% | — |
| MMLU-ProX | 81% | — |
| Mathematics | ||
| AIME 2023 | 84% | — |
| AIME 2024 | 86% | — |
| AIME 2025 | 85% | — |
| HMMT Feb 2023 | 80% | — |
| HMMT Feb 2024 | 82% | — |
| HMMT Feb 2025 | 81% | — |
| BRUMO 2025 | 83% | — |
| MATH-500 | 81% | — |
Holo3-35B-A3B is ahead overall, 78 to 62. The biggest single separator in this matchup is OSWorld-Verified, where the scores are 55% and 77.8%.
Holo3-35B-A3B has the edge for agentic tasks in this comparison, averaging 77.8 versus 58.8. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
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.