batiai/gemma-4-E2B-it-GGUF

Gemma 4 E2B-it GGUF — Quantized by BatiAI

<p align="center"> <a href="https://flow.bati.ai"><img src="https://img.shields.io/badge/BatiFlow-macOS%20AI%20Automation-blue?style=for-the-badge&logo=apple" alt="BatiFlow"></a> <a href="https://ollama.com/batiai/gemma4-e2b"><img src="https://img.shields.io/badge/Ollama-batiai%2Fgemma4--e2b-green?style=for-the-badge" alt="Ollama"></a> <a href="https://huggingface.co/google/gemma-4-E2B-it"><img src="https://img.shields.io/badge/Upstream-Gemma%204%20E2B--it-orange?style=for-the-badge" alt="Upstream"></a> </p>

Optimized GGUF quantizations of google/gemma-4-E2B-it — Google's tiniest fully-multimodal Gemma 4 (text + image + audio) for on-device AI on Mac. Built directly from official Google BF16 weights by BatiAI for BatiFlow.

The "E" stands for Edge. Tiny enough to run on basically any Mac (8 GB+) while still understanding speech and images alongside text — the only Gemma 4 size with audio support shared with E4B.

Quick Start

# Recommended
ollama pull batiai/gemma4-e2b:q4

# Higher quality
ollama pull batiai/gemma4-e2b:q6

Available Quantizations

Sub-3 B models stay sharp at Q4 — quantization noise is tiny relative to model capacity.

Two modes — text-only by default, multimodal opt-in

Upstream Gemma 4 E2B-it is fully multimodal — text + image + audio in one model. In the GGUF ecosystem this is delivered as two files: a main model.gguf (text tower) and a separate mmproj.gguf that holds both vision and audio encoders together (a single 1411-tensor projector covering image and speech input).

Multimodal usage (llama.cpp)

# Pick a main model (text tower)
wget https://huggingface.co/batiai/Gemma-4-E2B-it-GGUF/resolve/main/google-gemma-4-E2B-it-Q4_K_M.gguf

# Get the multimodal projector (vision + audio in one file)
wget https://huggingface.co/batiai/Gemma-4-E2B-it-GGUF/resolve/main/mmproj-BF16.gguf

Server mode (image input via OpenAI-compatible Vision API):

llama-server \
  -m google-gemma-4-E2B-it-Q4_K_M.gguf \
  --mmproj mmproj-BF16.gguf \
  -c 32768 --host 127.0.0.1 --port 8080

curl http://127.0.0.1:8080/v1/chat/completions -d '{
  "messages": [{
    "role": "user",
    "content": [
      {"type": "image_url", "image_url": {"url": "data:image/jpeg;base64,..."}},
      {"type": "text", "text": "What does this show?"}
    ]
  }]
}'

One-shot CLI with image:

llama-mtmd-cli \
  -m google-gemma-4-E2B-it-Q4_K_M.gguf \
  --mmproj mmproj-BF16.gguf \
  --image ~/Desktop/photo.jpg \
  -p "describe this image"

One-shot CLI with audio:

llama-mtmd-cli \
  -m google-gemma-4-E2B-it-Q4_K_M.gguf \
  --mmproj mmproj-BF16.gguf \
  --audio ~/Downloads/voice.wav \
  -p "transcribe and summarize"

mmproj quantization

Why E series (E2B / E4B) vs 26B / 31B?

If you need voice + image + text in one model on a small Mac, E series is the only Gemma 4 option.

Why BatiAI?

About BatiFlow

<p align="center"> <a href="https://flow.bati.ai"><strong>flow.bati.ai</strong></a> </p>

BatiFlow is a macOS-native AI desktop automation app — just 5 MB, built with Swift.

• —Free & Unlimited — On-device AI via Ollama, no API costs
• —100 % Private — All data stays on your Mac
• —Ultra Lightweight — Native macOS app, only 5 MB
• —57 built-in tools — calendar, notes, reminders, files, email, browser, messaging, and more

Related models in the BatiAI Gemma 4 lineup

Technical Details

• —Original Model: google/gemma-4-E2B-it
• —Architecture: Gemma 4 (Edge variant)
• —Modalities: Text (primary) + Image + Audio (via opt-in mmproj)
• —License: Gemma (commercial use permitted under terms)
• —Quantized with: llama.cpp
• —Quantized by: BatiAI
• —GGUF metadata: general.author: BatiAI, general.url: https://flow.bati.ai

License

Mirrors the upstream Gemma license. Commercial use permitted per Google's Gemma terms.

BatiAI's quantization pipeline is provided under MIT.