Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Granite-4.0-350M
~27
0/8 categoriesPhi-4
40
Winner · 2/8 categoriesGranite-4.0-350M· Phi-4
Pick Phi-4 if you want the stronger benchmark profile. Granite-4.0-350M only becomes the better choice if you need the larger 32K context window.
Phi-4 is clearly ahead on the aggregate, 40 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Phi-4's sharpest advantage is in multilingual, where it averages 67.2 against 16.2. The single biggest benchmark swing on the page is MGSM, 16.2% to 80.6%.
Granite-4.0-350M gives you the larger context window at 32K, compared with 16K for Phi-4.
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 | Phi-4 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 44% |
| BrowseComp | — | 35% |
| OSWorld-Verified | — | 34% |
| Coding | ||
| HumanEval | 38% | 82.6% |
| SWE-bench Pro | — | 55% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 54% |
| OfficeQA Pro | — | 38% |
| Reasoning | ||
| BBH | 33.3% | — |
| LongBench v2 | — | 30% |
| MRCRv2 | — | 33% |
| KnowledgePhi-4 wins | ||
| MMLU | 36.2% | 84.8% |
| GPQA | 26.1% | 56.1% |
| MMLU-Pro | 14.4% | — |
| FrontierScience | — | 52% |
| Instruction Following | ||
| IFEval | 61.6% | — |
| MultilingualPhi-4 wins | ||
| MGSM | 16.2% | 80.6% |
| MMLU-ProX | — | 60% |
| Mathematics | ||
| MATH-500 | — | 94.6% |
Phi-4 is ahead overall, 40 to 27. The biggest single separator in this matchup is MGSM, where the scores are 16.2% and 80.6%.
Phi-4 has the edge for knowledge tasks in this comparison, averaging 53.6 versus 18.5. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Phi-4 has the edge for multilingual tasks in this comparison, averaging 67.2 versus 16.2. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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