Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Granite-4.0-H-1B
~43
Winner · 0/8 categoriesNemotron Ultra 253B
41
3/8 categoriesGranite-4.0-H-1B· Nemotron Ultra 253B
Pick Granite-4.0-H-1B if you want the stronger benchmark profile. Nemotron Ultra 253B only becomes the better choice if multilingual is the priority or you want the stronger reasoning-first profile.
Granite-4.0-H-1B has the cleaner overall profile here, landing at 43 versus 41. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Nemotron Ultra 253B is the reasoning model in the pair, while Granite-4.0-H-1B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Granite-4.0-H-1B gives you the larger context window at 128K, compared with 32K for Nemotron Ultra 253B.
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-1B | Nemotron Ultra 253B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 46% |
| BrowseComp | — | 50% |
| OSWorld-Verified | — | 45% |
| Coding | ||
| HumanEval | 74% | 41% |
| SWE-bench Verified | — | 31% |
| LiveCodeBench | — | 30% |
| SWE-bench Pro | — | 38% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 37% |
| OfficeQA Pro | — | 54% |
| Reasoning | ||
| BBH | 60.4% | 77% |
| MuSR | — | 45% |
| LongBench v2 | — | 55% |
| MRCRv2 | — | 56% |
| KnowledgeNemotron Ultra 253B wins | ||
| MMLU | 59.4% | 49% |
| GPQA | 29.9% | 48% |
| MMLU-Pro | 34.0% | 63% |
| SuperGPQA | — | 46% |
| HLE | — | 11% |
| FrontierScience | — | 49% |
| SimpleQA | — | 47% |
| Instruction FollowingNemotron Ultra 253B wins | ||
| IFEval | 77.4% | 78% |
| MultilingualNemotron Ultra 253B wins | ||
| MGSM | 37.8% | 74% |
| MMLU-ProX | — | 68% |
| Mathematics | ||
| AIME 2023 | — | 49% |
| AIME 2024 | — | 51% |
| AIME 2025 | — | 50% |
| HMMT Feb 2023 | — | 45% |
| HMMT Feb 2024 | — | 47% |
| HMMT Feb 2025 | — | 46% |
| BRUMO 2025 | — | 48% |
| MATH-500 | — | 74% |
Granite-4.0-H-1B is ahead overall, 43 to 41. The biggest single separator in this matchup is MGSM, where the scores are 37.8% and 74%.
Nemotron Ultra 253B has the edge for knowledge tasks in this comparison, averaging 42.6 versus 32.6. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Nemotron Ultra 253B has the edge for instruction following in this comparison, averaging 78 versus 77.4. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Nemotron Ultra 253B has the edge for multilingual tasks in this comparison, averaging 70.1 versus 37.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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