Quick answer: Gemma 4 E2B is Google's December 2025 smallest on-device multimodal model with 2B effective parameters, scoring 60% MMLU-Pro. It succeeds Gemma 3n E2B (40.5% MMLU-Pro) with a significant +19.5pp improvement at the same parameter scale.
Where Gemma 4 E2B leads
Where it lags
Best for: Most resource-constrained on-device deployments; applications where E4B doesn't fit.
Gemma 4 E2B is Google's smallest model in the Gemma 4 family, targeting the most constrained on-device deployment scenarios. At 2B effective parameters, it achieves 60% MMLU-Pro — a substantial +19.5pp improvement over the predecessor Gemma 3n E2B (40.5%).
For most on-device applications, Gemma 4 E4B (69.4% MMLU-Pro) provides meaningfully better performance at comparable device footprint. E2B is reserved for devices where E4B is too large.
| Field | Value |
|---|---|
| Organization | |
| Effective parameters | 2B |
| License | Gemma Terms of Use |
| HuggingFace | google/gemma-4-E2B-it |
| Release date | December 2025 |
| Knowledge cutoff | September 2025 |
| Modality | Multimodal |
Open weights under Gemma Terms of Use — free to self-host.
| Benchmark | Score | Source | Date |
|---|---|---|---|
| MMLU-Pro | 60% | Benchgen evaluation | 2025-12 |
| Model | MMLU-Pro | Effective Params | License |
|---|---|---|---|
| Gemma 4 E2B | 60% | 2B | Gemma ToU |
| Gemma 3n E2B | 40.5% | 2B | Gemma ToU |
| Gemma 4 E4B | 69.4% | 4B | Gemma ToU |
Gemma 4 E2B vs Gemma 3n E2B: +19.5pp MMLU-Pro. vs Gemma 4 E4B: lower MMLU-Pro (60% vs 69.4%) but smaller footprint.
Specs from Google's Gemma 4 release (December 2025) and Benchgen evaluations. Last updated 2026-07-24.
This model isn’t on any benchmark leaderboard yet.