Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 1.0 Pro
41
Winner · 2/8 categoriesGranite-4.0-1B
~40
1/8 categoriesGemini 1.0 Pro· Granite-4.0-1B
Pick Gemini 1.0 Pro if you want the stronger benchmark profile. Granite-4.0-1B only becomes the better choice if instruction following is the priority or you need the larger 128K context window.
Gemini 1.0 Pro finishes one point ahead overall, 41 to 40. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Gemini 1.0 Pro's sharpest advantage is in multilingual, where it averages 66.8 against 27.5. The single biggest benchmark swing on the page is MGSM, 72% to 27.5%. Granite-4.0-1B does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
Granite-4.0-1B gives you the larger context window at 128K, compared with 32K for Gemini 1.0 Pro.
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 | Gemini 1.0 Pro | Granite-4.0-1B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 36% | — |
| BrowseComp | 51% | — |
| OSWorld-Verified | 36% | — |
| Coding | ||
| HumanEval | 54% | 73% |
| SWE-bench Verified | 5% | — |
| LiveCodeBench | 16% | — |
| SWE-bench Pro | 12% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 73% | — |
| OfficeQA Pro | 62% | — |
| Reasoning | ||
| MuSR | 58% | — |
| BBH | 73% | 59.7% |
| LongBench v2 | 51% | — |
| MRCRv2 | 54% | — |
| KnowledgeGemini 1.0 Pro wins | ||
| MMLU | 62% | 59.7% |
| GPQA | 62% | 29.7% |
| SuperGPQA | 60% | — |
| MMLU-Pro | 54% | 32.9% |
| HLE | 1% | — |
| FrontierScience | 54% | — |
| SimpleQA | 60% | — |
| Instruction FollowingGranite-4.0-1B wins | ||
| IFEval | 77% | 78.5% |
| MultilingualGemini 1.0 Pro wins | ||
| MGSM | 72% | 27.5% |
| MMLU-ProX | 64% | — |
| Mathematics | ||
| AIME 2023 | 62% | — |
| AIME 2024 | 64% | — |
| AIME 2025 | 63% | — |
| HMMT Feb 2023 | 58% | — |
| HMMT Feb 2024 | 60% | — |
| HMMT Feb 2025 | 59% | — |
| BRUMO 2025 | 61% | — |
| MATH-500 | 72% | — |
Gemini 1.0 Pro is ahead overall, 41 to 40. The biggest single separator in this matchup is MGSM, where the scores are 72% and 27.5%.
Gemini 1.0 Pro has the edge for knowledge tasks in this comparison, averaging 44.3 versus 31.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Granite-4.0-1B has the edge for instruction following in this comparison, averaging 78.5 versus 77. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Gemini 1.0 Pro has the edge for multilingual tasks in this comparison, averaging 66.8 versus 27.5. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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