Instructions to use hzang/Cosmos-Reason2-2B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use hzang/Cosmos-Reason2-2B-GGUF with Cosmos:

# No code snippets available yet for this library.

# To use this model, check the repository files and the library's documentation.

# Want to help? PRs adding snippets are welcome at:
# https://github.com/huggingface/huggingface.js

llama-cpp-python

How to use hzang/Cosmos-Reason2-2B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="hzang/Cosmos-Reason2-2B-GGUF",
	filename="Cosmos-Reason2-2B-Q4_K_M.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 hzang/Cosmos-Reason2-2B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf hzang/Cosmos-Reason2-2B-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 hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf hzang/Cosmos-Reason2-2B-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 hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use hzang/Cosmos-Reason2-2B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "hzang/Cosmos-Reason2-2B-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": "hzang/Cosmos-Reason2-2B-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/hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M

Ollama
How to use hzang/Cosmos-Reason2-2B-GGUF with Ollama:
```
ollama run hf.co/hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M
```

Unsloth Studio

How to use hzang/Cosmos-Reason2-2B-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 hzang/Cosmos-Reason2-2B-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 hzang/Cosmos-Reason2-2B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for hzang/Cosmos-Reason2-2B-GGUF to start chatting

How to use hzang/Cosmos-Reason2-2B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M

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": "hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use hzang/Cosmos-Reason2-2B-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 hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M

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 hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use hzang/Cosmos-Reason2-2B-GGUF with Docker Model Runner:
```
docker model run hf.co/hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M
```

Lemonade

How to use hzang/Cosmos-Reason2-2B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull hzang/Cosmos-Reason2-2B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Cosmos-Reason2-2B-GGUF-Q4_K_M

List all available models

lemonade list

Cosmos-Reason2-2B-GGUF

llama.cpp-compatible GGUF builds of nvidia/Cosmos-Reason2-2B, a 2.4B vision-language model post-trained from Qwen3-VL-2B-Instruct for physical-AI reasoning, spatial understanding, anomaly detection, and chain-of-thought scene analysis.

Files

File	Size	Notes
`Cosmos-Reason2-2B-Q4_K_M.gguf`	~1.28 GB	4-bit k-quant. Recommended for memory-constrained devices (e.g., iPhone 13+, 6 GB RAM).
`Cosmos-Reason2-2B-Q8_0.gguf`	~2.10 GB	8-bit quant. Recommended where memory allows (iPhone 15 Pro+ / 8 GB+).
`mmproj-Cosmos-Reason2-2B-F16.gguf`	~0.82 GB	Vision projector. Required for multimodal inference; load alongside either quant.

Usage with llama.cpp

llama-server \
    -m Cosmos-Reason2-2B-Q4_K_M.gguf \
    --mmproj mmproj-Cosmos-Reason2-2B-F16.gguf \
    --host 0.0.0.0 --port 8080 \
    -c 4096 --jinja

OpenAI-compatible endpoint at http://localhost:8080/v1. Standard chat/completions with image_url content blocks works out of the box.

Quality

Validated against the BF16 reference (nvidia/Cosmos-Reason2-2B) on a golden eval covering spatial reasoning, scene understanding, counting, OCR, anomaly detection, bounding-box output, and refusal. Q4_K_M scores 6/7 — equivalent to MLX Q4 — with the single discrepancy being an evaluator heuristic artifact, not a real quality regression.

Source / lineage

GGUF builds re-uploaded from Kbenkhaled/Cosmos-Reason2-2B-GGUF for hosting stability under the hzang/ account, alongside the MLX variants:

hzang/Cosmos-Reason2-2B-4bit — MLX 4-bit (1.78 GB)
hzang/Cosmos-Reason2-2B-8bit — MLX 8-bit (2.64 GB)
hzang/Cosmos-Reason2-2B-GGUF — llama.cpp GGUF (this repo)

License

NVIDIA Open Model License + Apache 2.0.

Downloads last month: 139

GGUF

Model size

2B params

Architecture

qwen3vl

Hardware compatibility

4-bit

8-bit

Model tree for hzang/Cosmos-Reason2-2B-GGUF

Base model

Qwen/Qwen3-VL-2B-Instruct

Finetuned

nvidia/Cosmos-Reason2-2B

Quantized

(14)

this model