Instructions to use zai-org/glm-edge-v-5b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zai-org/glm-edge-v-5b-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="zai-org/glm-edge-v-5b-gguf",
	filename="ggml-model-Q4_0.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "Describe this image in one sentence."
				},
				{
					"type": "image_url",
					"image_url": {
						"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
					}
				}
			]
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use zai-org/glm-edge-v-5b-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf zai-org/glm-edge-v-5b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf zai-org/glm-edge-v-5b-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf zai-org/glm-edge-v-5b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf zai-org/glm-edge-v-5b-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 zai-org/glm-edge-v-5b-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf zai-org/glm-edge-v-5b-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 zai-org/glm-edge-v-5b-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf zai-org/glm-edge-v-5b-gguf:Q4_K_M

Use Docker

docker model run hf.co/zai-org/glm-edge-v-5b-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use zai-org/glm-edge-v-5b-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zai-org/glm-edge-v-5b-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": "zai-org/glm-edge-v-5b-gguf",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/zai-org/glm-edge-v-5b-gguf:Q4_K_M

Ollama
How to use zai-org/glm-edge-v-5b-gguf with Ollama:
```
ollama run hf.co/zai-org/glm-edge-v-5b-gguf:Q4_K_M
```

Unsloth Studio new

How to use zai-org/glm-edge-v-5b-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 zai-org/glm-edge-v-5b-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 zai-org/glm-edge-v-5b-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for zai-org/glm-edge-v-5b-gguf to start chatting

Docker Model Runner
How to use zai-org/glm-edge-v-5b-gguf with Docker Model Runner:
```
docker model run hf.co/zai-org/glm-edge-v-5b-gguf:Q4_K_M
```

Lemonade

How to use zai-org/glm-edge-v-5b-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull zai-org/glm-edge-v-5b-gguf:Q4_K_M

Run and chat with the model

lemonade run user.glm-edge-v-5b-gguf-Q4_K_M

List all available models

lemonade list

Glm-Edge-V-5B-GGUF

中文阅读, 点击这里

Inference with Ollama

Installation

The code for adapting this model is actively being integrated into the official llama.cpp. You can test it using the following adapted version:

git clone https://github.com/piDack/llama.cpp -b support_glm_edge_model
cmake -B build -DGGML_CUDA=ON # Or enable other acceleration hardware
cmake --build build -- -j

Inference

After installation, you can start the GLM-Edge Chat model using the following command:

llama-cli -m <path>/model.gguf -p "<|user|>\nhi<|assistant|>\n" -ngl 999

In the command-line interface, you can interact with the model by entering your requests, and the model will provide the corresponding responses.

License

The usage of this model’s weights is subject to the terms outlined in the LICENSE.

Downloads last month: 463

GGUF

Model size

4B params

Architecture

chatglm

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

16-bit

Collection including zai-org/glm-edge-v-5b-gguf

GLM-Edge

Collection

10 items • Updated Jun 30, 2025 • 11