Compare
Gemma 4 E2B It vs Gemma 4 E4B IT
Put two to four models side by side on the fields that decide a deployment: context, price, region, license, languages, hosting, and what is verified.
| Gemma 4 E2B It | Gemma 4 E4B IT | |
|---|---|---|
| Provider | Google DeepMind | Google DeepMind |
| Parameters | 5.1B | 8B |
| Context window | Not verified: the provider has not documented this claim. | 131k |
| License | apache-2.0 | apache-2.0 |
| Modalities | text, vision, audio | text, vision, audio |
| Release date | 02 Mar 2026 | 02 Mar 2026 |
| Languages | Not verified: the provider has not documented this claim. | Strong: en, de, fr, es, it, pt Adequate: nl, pl, sv, cs, ro, el, uk, ru, ar, hi, zh, ja, ko, tr |
| Open weights | yes | yes |
| Tasks | Multilingual support, Low cost, Vision | Low cost, Vision, Multilingual support, Summarisation |
Where two models differ, this table shows the difference and stops. LLM EU publishes no winner badge without a documented score for that task, and a missing figure stays missing instead of becoming a zero.
When to use it
Gemma 4 E2B It
Strengths
- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- Apache-2.0 licence, so commercial self-hosting is permitted without a separate agreement
- at 5.1B parameters it fits on a single accelerator
- instruction-tuned checkpoint with a chat template in the repository
- speech recognition runs locally, so audio never leaves the operator premises
Limits
- catalogue only — LLM EU does not run this model, and nothing on this card implies an LLM EU endpoint
- no evaluation has been run by LLM EU
- the published configuration records no context window, so the card carries none
- at 5.1B parameters, the weights fit on a single modest accelerator
- vision checkpoints are heavier to serve than their parameter count alone suggests, because the image encoder and pre-processing run alongside the language model
Tasks
Gemma 4 E4B IT
Strengths
- native audio input in the small-model class
- Apache-2.0 licence
- runs on modest hardware
- text, image and audio in one checkpoint
Limits
- reasoning scores well below the larger Gemma 4 sizes
- 128K-token window, half of the medium models
- no evaluation has been run by LLM EU
Tasks
Tasks: Multilingual support, Low cost, Vision