Instructions to use bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-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 bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-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 bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-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 bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-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 bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-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 bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M

Use Docker

docker model run hf.co/bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-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": "bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-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/bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M

Ollama
How to use bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF with Ollama:
```
ollama run hf.co/bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M
```

Unsloth Studio

How to use bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-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 bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-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 bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF to start chatting

Docker Model Runner
How to use bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF with Docker Model Runner:
```
docker model run hf.co/bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M
```

Lemonade

How to use bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

vllm docker

by rcalv002 - opened Mar 24, 2025

Discussion

rcalv002

Mar 24, 2025

Hiya,

my stack uses vllm in docker. using huggingface cli I've downloaded the mistralai_Mistral-Small-3.1-24B-Instruct-2503-Q4_K_M.gguf into my standard huggingface hub cache, this is mounted to my vllm container (as with all the other models). When i try to run it, it fails. Are we missing some files in this repo?

  vllm:
    image: vllm/vllm-openai:latest
    runtime: nvidia
    command:
      - --model
      - bartowski/mistralai_Mistral-Small-3.1-24B-Instruct-2503-GGUF
      - --max_model_len
      - "8192"
      - --tokenizer_mode
      - mistral
      - --config_format
      - mistral
      - --load_format
      - mistral
      - --tool-call-parser
      - mistral
      - --enable-auto-tool-choice 
      - --host
      - 0.0.0.0
      - --port
      - "8000"
    ports:
      - "8000:8000"
    environment:
      - NVIDIA_VISIBLE_DEVICES=all
      - NVIDIA_DRIVER_CAPABILITIES=compute,utility
      - HF_TOKEN=${HF_TOKEN}
      - VLLM_API_KEY=${VLLM_API_KEY}
    volumes:
      - ~/.cache/huggingface:/root/.cache/huggingface

jophisbird

Mar 26, 2025

I'm having the same issue. Did you find any solutions to this?

bartowski

Owner Mar 26, 2025

it might be missing the type of the model? it's also possible vllm won't work at all, i know their GGUF support is still relatively beta-level

any reason for needing VLLM specifically?

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