Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Granite-4.0-H-350M
~24
0/8 categoriesPhi-4
40
Winner · 2/8 categoriesGranite-4.0-H-350M· Phi-4
Pick Phi-4 if you want the stronger benchmark profile. Granite-4.0-H-350M only becomes the better choice if you need the larger 32K context window.
Phi-4 is clearly ahead on the aggregate, 40 to 24. 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 14.7. The single biggest benchmark swing on the page is MGSM, 14.7% to 80.6%.
Granite-4.0-H-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-H-350M | Phi-4 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 44% |
| BrowseComp | — | 35% |
| OSWorld-Verified | — | 34% |
| Coding | ||
| HumanEval | 39% | 82.6% |
| SWE-bench Pro | — | 55% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 54% |
| OfficeQA Pro | — | 38% |
| Reasoning | ||
| BBH | 33.1% | — |
| LongBench v2 | — | 30% |
| MRCRv2 | — | 33% |
| KnowledgePhi-4 wins | ||
| MMLU | 35.0% | 84.8% |
| GPQA | 24.1% | 56.1% |
| MMLU-Pro | 12.1% | — |
| FrontierScience | — | 52% |
| Instruction Following | ||
| IFEval | 55.4% | — |
| MultilingualPhi-4 wins | ||
| MGSM | 14.7% | 80.6% |
| MMLU-ProX | — | 60% |
| Mathematics | ||
| MATH-500 | — | 94.6% |
Phi-4 is ahead overall, 40 to 24. The biggest single separator in this matchup is MGSM, where the scores are 14.7% and 80.6%.
Phi-4 has the edge for knowledge tasks in this comparison, averaging 53.6 versus 16.4. 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 14.7. Inside this category, MGSM 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.