Instructions to use stealth-model/GLM-5.3-Flash-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 stealth-model/GLM-5.3-Flash-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 stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS
# Run inference directly in the terminal:
llama cli -hf stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS
# Run inference directly in the terminal:
llama cli -hf stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

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 stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS
# Run inference directly in the terminal:
./llama-cli -hf stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

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 stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS
# Run inference directly in the terminal:
./build/bin/llama-cli -hf stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

Use Docker

docker model run hf.co/stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

Llama new
LM Studio
Jan

vLLM

How to use stealth-model/GLM-5.3-Flash-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "stealth-model/GLM-5.3-Flash-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": "stealth-model/GLM-5.3-Flash-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

Ollama
How to use stealth-model/GLM-5.3-Flash-GGUF with Ollama:
```
ollama run hf.co/stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS
```
Unsloth Desktop

How to use stealth-model/GLM-5.3-Flash-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

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": "stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use stealth-model/GLM-5.3-Flash-GGUF with Docker Model Runner:
```
docker model run hf.co/stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS
```

Lemonade

How to use stealth-model/GLM-5.3-Flash-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

Run and chat with the model

lemonade run user.GLM-5.3-Flash-GGUF-IQ2_XXS

List all available models

lemonade list

Hermes Agent

How to use stealth-model/GLM-5.3-Flash-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 stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

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 stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use stealth-model/GLM-5.3-Flash-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS

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 "stealth-model/GLM-5.3-Flash-GGUF:IQ2_XXS" \
  --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"

GLM-5.3-Flash was Ox Alpha. Two GGUF files, ready for llama.cpp.

By Stealth Models, who tracked it as Ox Alpha before Z.ai revealed it.

StealthMark results for GLM-5.3-Flash (Ox Alpha):

Compare it with Qwen3.8-27B, the best local model in our tests

Files as text

File	Size	Pick it for
`Q5_K_XL/`	240 GB in 6 parts	Near full quality, on machines with 256 GB or more of combined memory
`IQ2_XXS/`	102 GB in 4 parts	The smallest size we recommend: 128 GB machines such as a 128 GB Mac, DGX Spark or Strix Halo, or a 32 GB GPU with 96 GB of RAM
`mmproj-F16.gguf`	1.1 GB	Image input, full precision
`mmproj-Q8_0.gguf`	0.62 GB	Image input, near lossless
`mmproj-Q6_K.gguf`	0.49 GB	Image input, smaller
`mmproj-Q4_K.gguf`	0.34 GB	Image input, smallest

Run it

Download one size:

hf download stealth-model/GLM-5.3-Flash-GGUF --include "IQ2_XXS/*" "mmproj-Q8_0.gguf" --local-dir GLM-5.3-Flash

Point llama.cpp at the first part; it loads the rest:

llama-server -m GLM-5.3-Flash/IQ2_XXS/GLM-5.3-Flash-IQ2_XXS-00001-of-00004.gguf --mmproj GLM-5.3-Flash/mmproj-Q8_0.gguf --jinja

If the model is larger than your GPU, keep its expert layers in system RAM with --n-cpu-moe.

License

MIT, from Z.ai's GLM-5.3-Flash. The license file is included.

Ox Alpha card · StealthMark leaderboard · Follow us
Text and images: CC BY 4.0, stealthmodels.com.

Downloads last month: -

GGUF

Model size

321B params

Architecture

glm5-next

Hardware compatibility

2-bit

5-bit

Model tree for stealth-model/GLM-5.3-Flash-GGUF

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