batiai/ gemma4-e4b

129 Downloads Updated yesterday

tools thinking

ollama run batiai/gemma4-e4b:q4

curl http://localhost:11434/api/chat \
  -d '{
    "model": "batiai/gemma4-e4b:q4",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='batiai/gemma4-e4b:q4',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'batiai/gemma4-e4b:q4',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Applications

Claude Code

Claude Code ollama launch claude --model batiai/gemma4-e4b:q4

Codex

Codex ollama launch codex --model batiai/gemma4-e4b:q4

OpenCode

OpenCode ollama launch opencode --model batiai/gemma4-e4b:q4

OpenClaw

OpenClaw ollama launch openclaw --model batiai/gemma4-e4b:q4

Models

Name

2 models

Size

Context

Input

gemma4-e4b:q4

5.3GB · 128K context window · Text · yesterday

gemma4-e4b:q4

5.3GB

128K

Text

gemma4-e4b:q6

6.2GB · 128K context window · Text · yesterday

gemma4-e4b:q6

6.2GB

128K

Text

Readme

Gemma 4 E4B — 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)	5.0GB	10GB	57.1 t/s ✅	84.0 t/s	16GB Mac recommended
q6	5.8GB	11GB	45.0 t/s ✅	77.4 t/s	16GB Mac, higher quality

Quick Start

ollama run batiai/gemma4-e4b

Why Gemma 4 E4B?

8B total params, 4.5B 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
Smarter than E2B — passes tool calling on 16GB Mac
57 t/s on Mac mini M4 — fast enough for real-time use
Gemma license (free for most uses)

Model Comparison

Model	Size	VRAM	16GB Mac mini M4	Tool Call
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	✅
gemma4:e4b (official)	9.6GB	—	27.7 t/s	✅

BatiAI E4B Q4 is half the size of official gemma4:e4b, 2x faster, with tool calling support.

16GB Mac Users

Q4 recommended — 10GB VRAM, 57 t/s, best balance
Q6 also works — 11GB VRAM, 45 t/s, higher quality, tested and verified

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 E4B — 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) | **5.0GB** | **10GB** | **57.1 t/s** ✅ | 84.0 t/s | **16GB Mac recommended** |
| q6 | 5.8GB | 11GB | 45.0 t/s ✅ | 77.4 t/s | 16GB Mac, higher quality |

## Quick Start

```
ollama run batiai/gemma4-e4b
```

## Why Gemma 4 E4B?

- 8B total params, 4.5B 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
- Smarter than E2B — passes tool calling on 16GB Mac
- 57 t/s on Mac mini M4 — fast enough for real-time use
- Gemma license (free for most uses)

## Model Comparison

| Model | Size | VRAM | 16GB Mac mini M4 | Tool Call |
|-------|------|------|-------------------|-----------|
| 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 | ✅ |
| gemma4:e4b (official) | 9.6GB | — | 27.7 t/s | ✅ |

BatiAI E4B Q4 is half the size of official `gemma4:e4b`, 2x faster, with tool calling support.

## 16GB Mac Users

- **Q4 recommended** — 10GB VRAM, 57 t/s, best balance
- **Q6 also works** — 11GB VRAM, 45 t/s, higher quality, tested and verified

## 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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