Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Granite-4.0-350M
~27
Winner · 0/8 categoriesHolo2-8B
Coming soon
0/8 categoriesGranite-4.0-350M· Holo2-8B
Benchmark data for Granite-4.0-350M and Holo2-8B is coming soon on BenchLM.
BenchLM does not have sourced benchmark coverage for Holo2-8B yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Holo2-8B has the larger context window at 262K, compared with 32K for Granite-4.0-350M.
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 | Granite-4.0-350M | Holo2-8B |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| HumanEval | 38% | — |
| Multimodal & Grounded | ||
| Coming soon | ||
| Reasoning | ||
| BBH | 33.3% | — |
| Knowledge | ||
| MMLU | 36.2% | — |
| GPQA | 26.1% | — |
| MMLU-Pro | 14.4% | — |
| Instruction Following | ||
| IFEval | 61.6% | — |
| Multilingual | ||
| MGSM | 16.2% | — |
| 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.
Granite-4.0-350M: $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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