Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DBRX Instruct
41
Winner · 2/8 categoriesGranite-4.0-1B
~40
0/8 categoriesDBRX Instruct· Granite-4.0-1B
Pick DBRX Instruct if you want the stronger benchmark profile. Granite-4.0-1B only becomes the better choice if you need the larger 128K context window.
DBRX Instruct 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.
DBRX Instruct's sharpest advantage is in knowledge, where it averages 52 against 31.7. The single biggest benchmark swing on the page is MMLU, 73.7% to 59.7%.
Granite-4.0-1B gives you the larger context window at 128K, compared with 32K for DBRX Instruct.
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 | DBRX Instruct | Granite-4.0-1B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 41% | — |
| BrowseComp | 31% | — |
| OSWorld-Verified | 29% | — |
| Coding | ||
| HumanEval | 70.1% | 73% |
| SWE-bench Pro | 48% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 36% | — |
| OfficeQA Pro | 35% | — |
| Reasoning | ||
| LongBench v2 | 36% | — |
| MRCRv2 | 37% | — |
| BBH | — | 59.7% |
| KnowledgeDBRX Instruct wins | ||
| MMLU | 73.7% | 59.7% |
| FrontierScience | 52% | — |
| GPQA | — | 29.7% |
| MMLU-Pro | — | 32.9% |
| Instruction Following | ||
| IFEval | — | 78.5% |
| MultilingualDBRX Instruct wins | ||
| MMLU-ProX | 46% | — |
| MGSM | — | 27.5% |
| Mathematics | ||
| Coming soon | ||
DBRX Instruct is ahead overall, 41 to 40. The biggest single separator in this matchup is MMLU, where the scores are 73.7% and 59.7%.
DBRX Instruct has the edge for knowledge tasks in this comparison, averaging 52 versus 31.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DBRX Instruct has the edge for multilingual tasks in this comparison, averaging 46 versus 27.5. Granite-4.0-1B stays close enough that the answer can still flip depending on your workload.
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