Instructions to use phaseonx11/GLM-5.2-Uncensored-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use phaseonx11/GLM-5.2-Uncensored-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="phaseonx11/GLM-5.2-Uncensored-GGUF",
	filename="glm52-BF16-00001-of-00038.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use phaseonx11/GLM-5.2-Uncensored-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 phaseonx11/GLM-5.2-Uncensored-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf phaseonx11/GLM-5.2-Uncensored-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

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 phaseonx11/GLM-5.2-Uncensored-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

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 phaseonx11/GLM-5.2-Uncensored-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

Use Docker

docker model run hf.co/phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

LM Studio
Jan

vLLM

How to use phaseonx11/GLM-5.2-Uncensored-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "phaseonx11/GLM-5.2-Uncensored-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": "phaseonx11/GLM-5.2-Uncensored-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

Ollama
How to use phaseonx11/GLM-5.2-Uncensored-GGUF with Ollama:
```
ollama run hf.co/phaseonx11/GLM-5.2-Uncensored-GGUF:BF16
```

Unsloth Studio

How to use phaseonx11/GLM-5.2-Uncensored-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 phaseonx11/GLM-5.2-Uncensored-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 phaseonx11/GLM-5.2-Uncensored-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for phaseonx11/GLM-5.2-Uncensored-GGUF to start chatting

How to use phaseonx11/GLM-5.2-Uncensored-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "phaseonx11/GLM-5.2-Uncensored-GGUF:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use phaseonx11/GLM-5.2-Uncensored-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 phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

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 phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use phaseonx11/GLM-5.2-Uncensored-GGUF with Docker Model Runner:
```
docker model run hf.co/phaseonx11/GLM-5.2-Uncensored-GGUF:BF16
```

Lemonade

How to use phaseonx11/GLM-5.2-Uncensored-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull phaseonx11/GLM-5.2-Uncensored-GGUF:BF16

Run and chat with the model

lemonade run user.GLM-5.2-Uncensored-GGUF-BF16

List all available models

lemonade list

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

This is a quantized redistribution of a gated research artifact with reduced refusal behavior. By requesting access you affirm that you are of legal age in your jurisdiction, that you will not use it to generate CSAM, CBRN, or mass-harm content, and that you accept the original model license and disclaimer.

GLM-5.2-Uncensored - GGUF

As a reaction to the CEO of a fronteir model lobbying the media + congress to boogeyman open source models, I release:

Imatrix GGUF quantizations of zandenAI/GLM-5.2-FP8-Uncensored, an abliterated (refusal-removed) build of zai-org/GLM-5.2-FP8 - a 754B-parameter Mixture-of-Experts model.

All credit for the abliteration methodology and the source weights goes to Zanden Kane (@zandenkane). This repository only provides GGUF conversions for local inference.

Method

Source: FP8 -> dequantized to BF16 -> GGUF (the BF16 source is included here).
Quants: built with an importance matrix (imatrix) and a dynamic, MoE-aware recipe - experts at the target bit-width, with token-embeddings / output / attention kept higher (Q8_0 / Q6_K).
Calibration: standard public imatrix calibration corpus.

Files

File	Type	~Size	Notes
`glm52-BF16-*.gguf`	BF16	~1.5 TB	full-precision source; re-quant from this
`glm52-IQ1_M.gguf`	IQ1_M	~180 GB	smallest; big-RAM / Mac
`glm52-IQ2_M.gguf`	IQ2_M	~250 GB
`glm52-IQ3_XXS.gguf`	IQ3_XXS	~290 GB
`glm52-IQ4_XS.gguf`	IQ4_XS	~400 GB	best quality-per-byte at 4-bit
`glm52-Q4_K_M.gguf`	Q4_K_M	~450 GB	robust 4-bit default
`glm52-Q6_K.gguf`	Q6_K	~617 GB	near-lossless
`glm52.imatrix`	imatrix	small	roll your own quant levels

(Quants upload as they finish - some may still be in progress.)

Run with llama.cpp

./llama-server -m glm52-IQ4_XS.gguf -ngl 99 -c 16384 --host 0.0.0.0 --port 8080

For the sharded BF16, download all parts and point llama.cpp at the first shard; it auto-loads the rest.

Hardware guide

Quant	Fits on
IQ1_M / IQ2_M	256 GB RAM box, 192-256 GB Mac, or 3-4x A100
IQ3_XXS / IQ4_XS	384-512 GB RAM, 512 GB Mac, or 6-8x A100
Q4_K_M / Q6_K	8x A100 / H100, or large-RAM CPU/offload

Safety

The source model removes general refusals but preserves categorical refusal for CSAM / minor-exploitation content. Use responsibly and in accordance with your local laws. The original license and disclaimer apply in full.

License

MIT (inherited from the base model).

Credits

Base model: Z.ai / zai-org - GLM-5.2-FP8
Abliteration + source weights: Zanden Kane - zandenAI/GLM-5.2-FP8-Uncensored
GGUF conversion (imatrix + dynamic recipe): this repository

Downloads last month: -

GGUF

Model size

753B params

Architecture

glm-dsa

Hardware compatibility

16-bit

Model tree for phaseonx11/GLM-5.2-Uncensored-GGUF

Base model

zai-org/GLM-5.2-FP8

Quantized

zandenAI/GLM-5.2-FP8-Uncensored

Quantized

(1)

this model