Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4 Turbo
45
Winner · 3/8 categoriesGranite-4.0-H-350M
~24
0/8 categoriesGPT-4 Turbo· Granite-4.0-H-350M
Pick GPT-4 Turbo if you want the stronger benchmark profile. Granite-4.0-H-350M only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-4 Turbo is clearly ahead on the aggregate, 45 to 24. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4 Turbo's sharpest advantage is in multilingual, where it averages 65 against 14.7. The single biggest benchmark swing on the page is BBH, 75% to 33.1%.
GPT-4 Turbo gives you the larger context window at 128K, compared with 32K for Granite-4.0-H-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 | GPT-4 Turbo | Granite-4.0-H-350M |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 42% | — |
| BrowseComp | 54% | — |
| OSWorld-Verified | 41% | — |
| Coding | ||
| HumanEval | 52% | 39% |
| SWE-bench Verified | 5% | — |
| LiveCodeBench | 23% | — |
| SWE-bench Pro | 14% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 53% | — |
| OfficeQA Pro | 58% | — |
| Reasoning | ||
| MuSR | 56% | — |
| BBH | 75% | 33.1% |
| LongBench v2 | 62% | — |
| MRCRv2 | 62% | — |
| KnowledgeGPT-4 Turbo wins | ||
| MMLU | 60% | 35.0% |
| GPQA | 60% | 24.1% |
| SuperGPQA | 58% | — |
| MMLU-Pro | 51% | 12.1% |
| FrontierScience | 52% | — |
| SimpleQA | 58% | — |
| Instruction FollowingGPT-4 Turbo wins | ||
| IFEval | 80% | 55.4% |
| MultilingualGPT-4 Turbo wins | ||
| MMLU-ProX | 65% | — |
| MGSM | — | 14.7% |
| Mathematics | ||
| AIME 2023 | 60% | — |
| AIME 2024 | 62% | — |
| AIME 2025 | 61% | — |
| HMMT Feb 2023 | 56% | — |
| HMMT Feb 2024 | 58% | — |
| HMMT Feb 2025 | 57% | — |
| BRUMO 2025 | 59% | — |
| MATH-500 | 71% | — |
GPT-4 Turbo is ahead overall, 45 to 24. The biggest single separator in this matchup is BBH, where the scores are 75% and 33.1%.
GPT-4 Turbo has the edge for knowledge tasks in this comparison, averaging 54.9 versus 16.4. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
GPT-4 Turbo has the edge for instruction following in this comparison, averaging 80 versus 55.4. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-4 Turbo has the edge for multilingual tasks in this comparison, averaging 65 versus 14.7. Granite-4.0-H-350M stays close enough that the answer can still flip depending on your workload.
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