Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4.1
64
Winner · 3/8 categoriesGranite-4.0-1B
~40
0/8 categoriesGPT-4.1· Granite-4.0-1B
Pick GPT-4.1 if you want the stronger benchmark profile. Granite-4.0-1B only becomes the better choice if you want the cheaper token bill.
GPT-4.1 is clearly ahead on the aggregate, 64 to 40. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1's sharpest advantage is in multilingual, where it averages 69 against 27.5. The single biggest benchmark swing on the page is GPQA, 66.3% to 29.7%.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Granite-4.0-1B. That is roughly Infinityx on output cost alone. GPT-4.1 gives you the larger context window at 1M, compared with 128K for Granite-4.0-1B.
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-4.1 | Granite-4.0-1B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 61% | — |
| BrowseComp | 73% | — |
| OSWorld-Verified | 63% | — |
| Coding | ||
| SWE-bench Verified | 54.6% | — |
| SWE-bench Pro | 51% | — |
| HumanEval | — | 73% |
| Multimodal & Grounded | ||
| MMMU-Pro | 70% | — |
| OfficeQA Pro | 78% | — |
| Reasoning | ||
| LongBench v2 | 80% | — |
| MRCRv2 | 82% | — |
| BBH | — | 59.7% |
| KnowledgeGPT-4.1 wins | ||
| MMLU | 90.2% | 59.7% |
| GPQA | 66.3% | 29.7% |
| FrontierScience | 61% | — |
| MMLU-Pro | — | 32.9% |
| Instruction FollowingGPT-4.1 wins | ||
| IFEval | 87.4% | 78.5% |
| MultilingualGPT-4.1 wins | ||
| MMLU-ProX | 69% | — |
| MGSM | — | 27.5% |
| Mathematics | ||
| AIME 2024 | 26.4% | — |
GPT-4.1 is ahead overall, 64 to 40. The biggest single separator in this matchup is GPQA, where the scores are 66.3% and 29.7%.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 63.1 versus 31.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for instruction following in this comparison, averaging 87.4 versus 78.5. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for multilingual tasks in this comparison, averaging 69 versus 27.5. Granite-4.0-1B stays close enough that the answer can still flip depending on your workload.
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