Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E4B
~47
Winner · 0/8 categoriesHolo2-8B
~0
0/8 categoriesGemma 4 E4B· Holo2-8B
Benchmark data for Gemma 4 E4B and Holo2-8B is coming soon on BenchLM.
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Holo2-8B has the larger context window at 262K, compared with 128K for Gemma 4 E4B.
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 E4B | Holo2-8B |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| LiveCodeBench | 52% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 52.6% | — |
| ScreenSpot Pro | — | 58.9% |
| Reasoning | ||
| BBH | 33.1% | — |
| MRCRv2 | 25.4% | — |
| Knowledge | ||
| GPQA | 58.6% | — |
| MMLU-Pro | 69.4% | — |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| Coming soon | ||
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
Gemma 4 E4B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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