Instructions to use ggml-org/AutoGLM-Phone-9B-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 ggml-org/AutoGLM-Phone-9B-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 ggml-org/AutoGLM-Phone-9B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ggml-org/AutoGLM-Phone-9B-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 ggml-org/AutoGLM-Phone-9B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ggml-org/AutoGLM-Phone-9B-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 ggml-org/AutoGLM-Phone-9B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ggml-org/AutoGLM-Phone-9B-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 ggml-org/AutoGLM-Phone-9B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ggml-org/AutoGLM-Phone-9B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/ggml-org/AutoGLM-Phone-9B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use ggml-org/AutoGLM-Phone-9B-GGUF with Ollama:
```
ollama run hf.co/ggml-org/AutoGLM-Phone-9B-GGUF:Q4_K_M
```

Unsloth Studio

How to use ggml-org/AutoGLM-Phone-9B-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 ggml-org/AutoGLM-Phone-9B-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 ggml-org/AutoGLM-Phone-9B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ggml-org/AutoGLM-Phone-9B-GGUF to start chatting

Docker Model Runner
How to use ggml-org/AutoGLM-Phone-9B-GGUF with Docker Model Runner:
```
docker model run hf.co/ggml-org/AutoGLM-Phone-9B-GGUF:Q4_K_M
```

Lemonade

How to use ggml-org/AutoGLM-Phone-9B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ggml-org/AutoGLM-Phone-9B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.AutoGLM-Phone-9B-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

which is the language version of this quantized model?

by blowtorch-971 - opened Dec 25, 2025

Discussion

blowtorch-971

Dec 25, 2025

•

edited Dec 25, 2025

I would like to know if this model has been quantized from the version optimized for Chinese mobile applications (as the name seems to imply and the tag for the original model suggests) or else if it was derived from the Multilingual one that supports English scenarios and is suitable for applications containing English or other language content, as stated here: https://github.com/zai-org/Open-AutoGLM/blob/main/README_en.md

Thanks

blowtorch-971 changed discussion title from which is the version of this quantized model? to which is the language version of this quantized model? Dec 25, 2025

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