batiai/ gemma4-e2b

180 Downloads Updated yesterday

tools thinking

ollama run batiai/gemma4-e2b:q4

curl http://localhost:11434/api/chat \
  -d '{
    "model": "batiai/gemma4-e2b:q4",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='batiai/gemma4-e2b:q4',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'batiai/gemma4-e2b:q4',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Applications

Claude Code

Claude Code ollama launch claude --model batiai/gemma4-e2b:q4

Codex

Codex ollama launch codex --model batiai/gemma4-e2b:q4

OpenCode

OpenCode ollama launch opencode --model batiai/gemma4-e2b:q4

OpenClaw

OpenClaw ollama launch openclaw --model batiai/gemma4-e2b:q4

Models

Name

2 models

Size

Context

Input

gemma4-e2b:q4

3.4GB · 128K context window · Text · yesterday

gemma4-e2b:q4

3.4GB

128K

Text

gemma4-e2b:q6

3.8GB · 128K context window · Text · yesterday

gemma4-e2b:q6

3.8GB

128K

Text

Readme

Gemma 4 E2B — Quantized by BatiAI

Quantized from official Google weights. Verified on real Mac hardware.

Models

Tag	Size	VRAM	16GB Mac mini M4	M4 Max (128GB)	Use Case
q4 (latest)	3.2GB	7.1GB	107.8 t/s ✅	132.5 t/s	16GB Mac recommended
q6	3.6GB	7.5GB	45.5 t/s ✅	117.5 t/s	Higher quality, fits 16GB

Quick Start

ollama run batiai/gemma4-e2b

Why Gemma 4 E2B?

5.1B total params, 2.3B effective — PLE (Per-Layer Embeddings) for on-device efficiency
Vision support included (mmproj) — describe images in chat
Audio: supported in original model, not yet in llama.cpp/Ollama ecosystem
128K context window
3.2GB Q4 fits comfortably in 16GB Mac — plenty of room for KV cache
107 t/s on Mac mini M4 — instant responses
Gemma license (free for most uses)

16GB Mac — The Lightest Option

Model	Size	VRAM	16GB Mac mini M4
batiai/gemma4-e2b:q4	3.2GB	7.1GB	107.8 t/s
batiai/gemma4-e4b:q4	5.0GB	10GB	57.1 t/s
batiai/qwen3.5-9b:q4	5.6GB	—	12.5 t/s

Gemma 4 E2B is the smallest and fastest model we ship — ideal for quick responses and low memory usage. For better tool calling accuracy, use E4B.

Why BatiAI?

Quantized directly from official Google weights (not third-party)
Q4_K_M and Q6_K — higher quality quant methods than default
Verified on Mac mini M4 (16GB) + MacBook Pro M4 Max (128GB)
Korean language and tool calling tested on real hardware

Built for BatiFlow

Free, on-device AI automation for Mac. 5MB app, 100% local, unlimited.

https://flow.bati.ai

# Gemma 4 E2B — Quantized by BatiAI

Quantized from official Google weights. Verified on real Mac hardware.

## Models

| Tag | Size | VRAM | 16GB Mac mini M4 | M4 Max (128GB) | Use Case |
|-----|------|------|-------------------|----------------|----------|
| **q4** (latest) | **3.2GB** | **7.1GB** | **107.8 t/s** ✅ | 132.5 t/s | **16GB Mac recommended** |
| q6 | 3.6GB | 7.5GB | 45.5 t/s ✅ | 117.5 t/s | Higher quality, fits 16GB |

## Quick Start

```
ollama run batiai/gemma4-e2b
```

## Why Gemma 4 E2B?

- 5.1B total params, 2.3B effective — PLE (Per-Layer Embeddings) for on-device efficiency
- Vision support included (mmproj) — describe images in chat
- Audio: supported in original model, not yet in llama.cpp/Ollama ecosystem
- 128K context window
- 3.2GB Q4 fits comfortably in 16GB Mac — plenty of room for KV cache
- 107 t/s on Mac mini M4 — instant responses
- Gemma license (free for most uses)

## 16GB Mac — The Lightest Option

| Model | Size | VRAM | 16GB Mac mini M4 |
|-------|------|------|-------------------|
| **batiai/gemma4-e2b:q4** | **3.2GB** | **7.1GB** | **107.8 t/s** |
| batiai/gemma4-e4b:q4 | 5.0GB | 10GB | 57.1 t/s |
| batiai/qwen3.5-9b:q4 | 5.6GB | — | 12.5 t/s |

Gemma 4 E2B is the smallest and fastest model we ship — ideal for quick responses and low memory usage. For better tool calling accuracy, use E4B.

## Why BatiAI?

- Quantized directly from official Google weights (not third-party)
- Q4_K_M and Q6_K — higher quality quant methods than default
- Verified on Mac mini M4 (16GB) + MacBook Pro M4 Max (128GB)
- Korean language and tool calling tested on real hardware

## Built for BatiFlow

Free, on-device AI automation for Mac. 5MB app, 100% local, unlimited.

https://flow.bati.ai

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