Instructions to use ggml-org/moondream2-20250414-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ggml-org/moondream2-20250414-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ggml-org/moondream2-20250414-GGUF",
	filename="moondream2-mmproj-f16-20250414.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use ggml-org/moondream2-20250414-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ggml-org/moondream2-20250414-GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf ggml-org/moondream2-20250414-GGUF:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ggml-org/moondream2-20250414-GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf ggml-org/moondream2-20250414-GGUF:F16

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/moondream2-20250414-GGUF:F16
# Run inference directly in the terminal:
./llama-cli -hf ggml-org/moondream2-20250414-GGUF:F16

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/moondream2-20250414-GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ggml-org/moondream2-20250414-GGUF:F16

Use Docker

docker model run hf.co/ggml-org/moondream2-20250414-GGUF:F16

LM Studio
Jan
Ollama
How to use ggml-org/moondream2-20250414-GGUF with Ollama:
```
ollama run hf.co/ggml-org/moondream2-20250414-GGUF:F16
```

Unsloth Studio

How to use ggml-org/moondream2-20250414-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/moondream2-20250414-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/moondream2-20250414-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/moondream2-20250414-GGUF to start chatting

Docker Model Runner
How to use ggml-org/moondream2-20250414-GGUF with Docker Model Runner:
```
docker model run hf.co/ggml-org/moondream2-20250414-GGUF:F16
```

Lemonade

How to use ggml-org/moondream2-20250414-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ggml-org/moondream2-20250414-GGUF:F16

Run and chat with the model

lemonade run user.moondream2-20250414-GGUF-F16

List all available models

lemonade list

This repo contains the llama.cpp compatible GGUFs of vikhyatk/moondream2: https://huggingface.co/vikhyatk/moondream2.

The GGUFs hosted in the original repo is missing the tokenizer.chat_template field, thanks to @Hahasb for adding the vicuna template.

For further discussion, please refer to the PR: https://github.com/ggml-org/llama.cpp/pull/13745

Downloads last month: 9,471

GGUF

Model size

1B params

Architecture

phi2

Hardware compatibility

16-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for ggml-org/moondream2-20250414-GGUF

Base model

vikhyatk/moondream2

Quantized

(7)

this model

Collection including ggml-org/moondream2-20250414-GGUF

Multimodal GGUFs

Collection

Vision and audio models compatible with llama-server and llama-mtmd-cli • 16 items • Updated Dec 18, 2025 • 21