Instructions to use BennyDaBall/Z-Image-Engineer-V6-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use BennyDaBall/Z-Image-Engineer-V6-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Use Docker

docker model run hf.co/BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use BennyDaBall/Z-Image-Engineer-V6-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "BennyDaBall/Z-Image-Engineer-V6-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BennyDaBall/Z-Image-Engineer-V6-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Ollama
How to use BennyDaBall/Z-Image-Engineer-V6-GGUF with Ollama:
```
ollama run hf.co/BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M
```

Unsloth Studio

How to use BennyDaBall/Z-Image-Engineer-V6-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for BennyDaBall/Z-Image-Engineer-V6-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for BennyDaBall/Z-Image-Engineer-V6-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for BennyDaBall/Z-Image-Engineer-V6-GGUF to start chatting

How to use BennyDaBall/Z-Image-Engineer-V6-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use BennyDaBall/Z-Image-Engineer-V6-GGUF with Docker Model Runner:
```
docker model run hf.co/BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M
```

Lemonade

How to use BennyDaBall/Z-Image-Engineer-V6-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Z-Image-Engineer-V6-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use BennyDaBall/Z-Image-Engineer-V6-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use BennyDaBall/Z-Image-Engineer-V6-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "BennyDaBall/Z-Image-Engineer-V6-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

BennyDaBall commited on Jun 12

Commit

89ffc15

verified ·

1 Parent(s): 53793db

README: document ComfyUI-Z-Engineer v2 GGUF loader + local enhancer

Browse files

Files changed (1) hide show

README.md +13 -8

README.md CHANGED Viewed

@@ -24,7 +24,7 @@ tags:
 GGUF quantized release for [Z-Image-Engineer V6](https://huggingface.co/BennyDaBall/Z-Image-Engineer-V6).
-The main repo contains the merged HF safetensors. This repo contains the quant ladder for LM Studio, ComfyUI `CLIPLoaderGGUF`, llama.cpp-style loaders, and local prompt-enhancement workflows.
 ![Z-Image-Engineer V6 simple A/B with rewrites](evidence/gallery_z_image_engineer_v6_simple_ab_with_rewrites_CONTACT.png)
@@ -36,8 +36,9 @@ The main repo contains the merged HF safetensors. This repo contains the quant l
 Use these GGUF files when you want:
 - LM Studio prompt enhancement
-- ComfyUI Z-Image text-encoder replacement through `CLIPLoaderGGUF`
 - smaller local files than the merged HF safetensors
 - the same V6 prompt style and conditioning behavior in a quantized format
@@ -71,12 +72,16 @@ Enhance this image prompt for Z-Image Turbo: a unicorn
 The comparison examples were generated from direct LM Studio user requests like this, with no separate system prompt. `V6_SYSTEM_PROMPT.md` is included only as an optional preset for people who want a stricter prompt-only chat setup.
-### ComfyUI
-1. Place a GGUF file into `ComfyUI/models/text_encoders/`.
-2. Add a `CLIPLoaderGGUF` node.
-3. Set model type to `lumina2`.
-4. Use it where the stock Z-Image Qwen text encoder would normally go.
 Verified image settings:
@@ -111,7 +116,7 @@ The final V6 build used master-corpus SMART DoRA training, retention pressure, S
 ## Related Repos
 - Main merged HF release: [BennyDaBall/Z-Image-Engineer-V6](https://huggingface.co/BennyDaBall/Z-Image-Engineer-V6)
-- Optional ComfyUI workflow repo: [ComfyUI-Z-Engineer](https://github.com/BennyDaBall930/ComfyUI-Z-Engineer)
 ---

 GGUF quantized release for [Z-Image-Engineer V6](https://huggingface.co/BennyDaBall/Z-Image-Engineer-V6).
+The main repo contains the merged HF safetensors. This repo contains the quant ladder for the [ComfyUI-Z-Engineer](https://github.com/BennyDaBall930/ComfyUI-Z-Engineer) node, LM Studio, ComfyUI `CLIPLoaderGGUF`, llama.cpp-style loaders, and local prompt-enhancement workflows.
 ![Z-Image-Engineer V6 simple A/B with rewrites](evidence/gallery_z_image_engineer_v6_simple_ab_with_rewrites_CONTACT.png)
 Use these GGUF files when you want:
+- ComfyUI Z-Image text-encoder replacement and in-ComfyUI prompt enhancement through [ComfyUI-Z-Engineer](https://github.com/BennyDaBall930/ComfyUI-Z-Engineer) (no external server needed)
 - LM Studio prompt enhancement
+- ComfyUI text-encoder loading through plain `CLIPLoaderGGUF`
 - smaller local files than the merged HF safetensors
 - the same V6 prompt style and conditioning behavior in a quantized format
 The comparison examples were generated from direct LM Studio user requests like this, with no separate system prompt. `V6_SYSTEM_PROMPT.md` is included only as an optional preset for people who want a stricter prompt-only chat setup.
+### ComfyUI (recommended: ComfyUI-Z-Engineer)
+1. Install the [ComfyUI-Z-Engineer](https://github.com/BennyDaBall930/ComfyUI-Z-Engineer) custom node (v2.0+).
+2. Place a GGUF file into `ComfyUI/models/text_encoders/`.
+3. Add **Z-Engineer CLIP Loader (GGUF)** and pick the quant - use the `clip` output where the stock Z-Image Qwen text encoder would normally go.
+4. Optional: add **Z-Engineer Prompt Enhancer (Local)** with the same `clip` to rewrite seed prompts in-process, previewed on the node. No LM Studio or external server required.
+A ready-made workflow ships with the node repo: `example_workflows/z_image_turbo_z_engineer.json`. With [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) installed the quant stays quantized in VRAM.
+Alternative without the node: add a plain `CLIPLoaderGGUF` node (ComfyUI-GGUF), set model type to `lumina2`, and use it as the text encoder only.
 Verified image settings:
 ## Related Repos
 - Main merged HF release: [BennyDaBall/Z-Image-Engineer-V6](https://huggingface.co/BennyDaBall/Z-Image-Engineer-V6)
+- ComfyUI custom node (GGUF + shard loaders, local prompt enhancer with preview): [ComfyUI-Z-Engineer](https://github.com/BennyDaBall930/ComfyUI-Z-Engineer)
 ---