Instructions to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF",
	filename="Mistral-Small-3.2-24B-Instruct-2506-BF16.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 Settings

llama.cpp

How to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama-cli -hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama-cli -hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

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 unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./llama-cli -hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

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 unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./build/bin/llama-cli -hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

Use Docker

docker model run hf.co/unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

LM Studio
Jan

vLLM

How to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "unsloth/Mistral-Small-3.2-24B-Instruct-2506-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": "unsloth/Mistral-Small-3.2-24B-Instruct-2506-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/unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

Ollama
How to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF with Ollama:
```
ollama run hf.co/unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL
```

Unsloth Studio

How to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-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 unsloth/Mistral-Small-3.2-24B-Instruct-2506-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 unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF to start chatting

How to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

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": "unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

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 unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

Run Hermes

hermes

Docker Model Runner
How to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF with Docker Model Runner:
```
docker model run hf.co/unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL
```

Lemonade

How to use unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:UD-Q4_K_XL

Run and chat with the model

lemonade run user.Mistral-Small-3.2-24B-Instruct-2506-GGUF-UD-Q4_K_XL

List all available models

lemonade list

How to enable the text+image to text mode? (i.e. add the vision encoder)

by Didier - opened Sep 4, 2025

Discussion

Didier

Sep 4, 2025

As always, it must be very simple once we know how to, but I currently do not know.

Question

How do I merge the GGUF file (text mode only) with the mmproj file (vision encoder)?
Text only: Mistral-Small-3.2-24B-Instruct-2506-Q4_0.gguf
Vision encoder: mmproj-BF16.gguf

What

I am interested in serving the multimodal (text+image) model as an OpenAI compatible API using the conda package llama-cpp-python.

Env

conda create -n model_serve llama-cpp-python ipykernel

Serving

python -m llama_cpp.server --model Mistral-Small-3.2-24B-Instruct-2506-Q4_0.gguf
--clip_model_path mmproj-BF16.gguf

Using (with LiteLLM)

Text to text mode is fine!
When text+image as input, I get a message indicating that there is no vision encoder :-(

"""
Please share the image you'd like me to describe. You can paste it directly into the chat, and I'll do my best to analyze its contents for you!
"""

Thanks for any help and your time.

Didier

Oct 20, 2025

Simply changed the way the model is served, i.e. using "-hf" instead of "--model xxxxx --clip-model xxxxx". Text+image to text works as expected. I.e.

llama-server -hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF --jinja --host 127.0.0.1 --port 8080 --api-key "Keep learning" --ctx-size 4096

Didier changed discussion status to closed Oct 20, 2025

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How to enable the **text+image to text** mode? (i.e. add the vision encoder)

How to enable the text+image to text mode? (i.e. add the vision encoder)