Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Holo3-122B-A10B
~79
Winner · 0/8 categoriesQwen2.5-VL-32B
~50
0/8 categoriesHolo3-122B-A10B· Qwen2.5-VL-32B
Benchmark data for Holo3-122B-A10B and Qwen2.5-VL-32B is coming soon on BenchLM.
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Holo3-122B-A10B is priced at $0.40 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen2.5-VL-32B. Holo3-122B-A10B has the larger context window at 64K, compared with 32K for Qwen2.5-VL-32B.
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 | Holo3-122B-A10B | Qwen2.5-VL-32B |
|---|---|---|
| Agentic | ||
| OSWorld-Verified | 78.8% | — |
| Coding | ||
| HumanEval | — | 91.5% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 49.5% |
| Reasoning | ||
| Coming soon | ||
| Knowledge | ||
| GPQA | — | 46% |
| MMLU-Pro | — | 68.8% |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| Coming soon | ||
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
Holo3-122B-A10B: $0.40 input / $3.00 output per 1M tokens Qwen2.5-VL-32B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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