Instructions to use ddh0/GLM-4.5-Iceblink-v2-106B-A12B-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 ddh0/GLM-4.5-Iceblink-v2-106B-A12B-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 ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL
# Run inference directly in the terminal:
llama cli -hf ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL
# Run inference directly in the terminal:
llama cli -hf ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

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 ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL
# Run inference directly in the terminal:
./llama-cli -hf ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

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 ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

Use Docker

docker model run hf.co/ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

LM Studio
Jan
Ollama
How to use ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF with Ollama:
```
ollama run hf.co/ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL
```
Unsloth Desktop

How to use ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

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": "ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF with Docker Model Runner:
```
docker model run hf.co/ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL
```

Lemonade

How to use ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

Run and chat with the model

lemonade run user.GLM-4.5-Iceblink-v2-106B-A12B-GGUF-IQ4_NL

List all available models

lemonade list

Hermes Agent

How to use ddh0/GLM-4.5-Iceblink-v2-106B-A12B-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 ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

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 ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL

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 "ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF:IQ4_NL" \
  --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-4.5-Iceblink-v2-106B-A12B-106B-A12B-GGUF

This repository contains several custom GGUF quantizations of zerofata/GLM-4.5-Iceblink-v2-106B-A12B, to be used with llama.cpp.

The naming scheme for these custom quantizations is as follows:

ModelName-DefaultType-FFN-UpType-GateType-DownType.gguf

Where DefaultType refers to the default tensor type, and UpType, GateType, and DownType refer to the tensor types used for the ffn_up_exps, ffn_gate_exps, and ffn_down_exps tensors respectively.

Quantizations

These quantizations use Q8_0 for all tensors by default, including the dense FFN block. Only the conditional experts are downgraded. The shared expert is always kept in Q8_0. They were quantized using my own imatrix (the calibration text corpus can be found here).

Filename	Size (GB)	Size (GiB)	Average BPW	Direct link
GLM-4.5-Iceblink-v2-106B-A12B-Q8_0-FFN-IQ4_XS-IQ3_S-IQ4_NL.gguf	60.94	56.76	4.41	Download
GLM-4.5-Iceblink-v2-106B-A12B-Q8_0-FFN-IQ4_XS-IQ4_XS-IQ4_NL.gguf	64.39	59.97	4.66	Download
GLM-4.5-Iceblink-v2-106B-A12B-Q8_0-FFN-IQ4_XS-IQ4_XS-Q5_0.gguf	68.63	63.92	4.97	Download
GLM-4.5-Iceblink-v2-106B-A12B-Q8_0-FFN-Q4_K-Q4_K-Q8_0.gguf	83.49	77.76	6.05	Download
GLM-4.5-Iceblink-v2-106B-A12B-Q8_0-FFN-Q5_K-Q5_K-Q8_0.gguf	91.97	85.66	6.66	Download
GLM-4.5-Iceblink-v2-106B-A12B-Q8_0-FFN-Q6_K-Q6_K-Q8_0.gguf	100.99	94.06	7.31	Download
GLM-4.5-Iceblink-v2-106B-A12B-Q8_0.gguf	117.45	109.38	8.51	Download
GLM-4.5-Iceblink-v2-106B-A12B-bf16.gguf	220.98	205.81	16.00	Download

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GGUF

Model size

110B params

Architecture

glm4moe

Hardware compatibility

4-bit

5-bit

8-bit

16-bit

View +1 variant

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Model tree for ddh0/GLM-4.5-Iceblink-v2-106B-A12B-GGUF

Base model

zai-org/GLM-4.5-Air

Finetuned

zerofata/GLM-4.5-Iceblink-v2-106B-A12B

Quantized

(7)

this model