Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 26B A4B
64
Winner · 1/8 categoriesGranite-4.0-H-350M
~22
0/8 categoriesGemma 4 26B A4B· Granite-4.0-H-350M
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. Granite-4.0-H-350M only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Gemma 4 26B A4B is clearly ahead on the aggregate, 64 to 22. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 26B A4B's sharpest advantage is in knowledge, where it averages 56.1 against 16.4. The single biggest benchmark swing on the page is MMLU-Pro, 82.6% to 12.1%.
Gemma 4 26B A4B is the reasoning model in the pair, while Granite-4.0-H-350M 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. Gemma 4 26B A4B gives you the larger context window at 256K, 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 | Gemma 4 26B A4B | Granite-4.0-H-350M |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| LiveCodeBench | 77.1% | — |
| HumanEval | — | 39% |
| Multimodal & Grounded | ||
| MMMU-Pro | 73.8% | — |
| Reasoning | ||
| BBH | 64.8% | 33.1% |
| MRCRv2 | 44.1% | — |
| KnowledgeGemma 4 26B A4B wins | ||
| GPQA | 82.3% | 24.1% |
| MMLU-Pro | 82.6% | 12.1% |
| HLE | 17.2% | — |
| HLE w/o tools | 8.7% | — |
| MMLU | — | 35.0% |
| Instruction Following | ||
| IFEval | — | 55.4% |
| Multilingual | ||
| MGSM | — | 14.7% |
| Mathematics | ||
| Coming soon | ||
Gemma 4 26B A4B is ahead overall, 64 to 22. The biggest single separator in this matchup is MMLU-Pro, where the scores are 82.6% and 12.1%.
Gemma 4 26B A4B has the edge for knowledge tasks in this comparison, averaging 56.1 versus 16.4. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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