Instructions to use antirez/deepseek-v4-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use antirez/deepseek-v4-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="antirez/deepseek-v4-gguf",
	filename="DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2-imatrix.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use antirez/deepseek-v4-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf antirez/deepseek-v4-gguf:F32
# Run inference directly in the terminal:
llama-cli -hf antirez/deepseek-v4-gguf:F32

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf antirez/deepseek-v4-gguf:F32
# Run inference directly in the terminal:
llama-cli -hf antirez/deepseek-v4-gguf:F32

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 antirez/deepseek-v4-gguf:F32
# Run inference directly in the terminal:
./llama-cli -hf antirez/deepseek-v4-gguf:F32

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 antirez/deepseek-v4-gguf:F32
# Run inference directly in the terminal:
./build/bin/llama-cli -hf antirez/deepseek-v4-gguf:F32

Use Docker

docker model run hf.co/antirez/deepseek-v4-gguf:F32

LM Studio
Jan

vLLM

How to use antirez/deepseek-v4-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "antirez/deepseek-v4-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": "antirez/deepseek-v4-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/antirez/deepseek-v4-gguf:F32

Ollama
How to use antirez/deepseek-v4-gguf with Ollama:
```
ollama run hf.co/antirez/deepseek-v4-gguf:F32
```

Unsloth Studio new

How to use antirez/deepseek-v4-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 antirez/deepseek-v4-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 antirez/deepseek-v4-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for antirez/deepseek-v4-gguf to start chatting

Pi new

How to use antirez/deepseek-v4-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf antirez/deepseek-v4-gguf:F32

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": "antirez/deepseek-v4-gguf:F32"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use antirez/deepseek-v4-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 antirez/deepseek-v4-gguf:F32

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 antirez/deepseek-v4-gguf:F32

Run Hermes

hermes

Docker Model Runner
How to use antirez/deepseek-v4-gguf with Docker Model Runner:
```
docker model run hf.co/antirez/deepseek-v4-gguf:F32
```

Lemonade

How to use antirez/deepseek-v4-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull antirez/deepseek-v4-gguf:F32

Run and chat with the model

lemonade run user.deepseek-v4-gguf-F32

List all available models

lemonade list

Can it be used?

by X-AI-GT - opened 29 days ago

Discussion

X-AI-GT

29 days ago

Can this be loaded by llama.cpp? Can it be used?

bisobiso

29 days ago

I tried on a Ubuntu Linux with 500 GB Ram but I obtain:
llama-cli -m DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2.gguf -cnv

Loading model... -llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'deepseek4'
llama_model_load_from_file_impl: failed to load model
common_fit_params: encountered an error while trying to fit params to free device memory: failed to load model \llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'deepseek4'
llama_model_load_from_file_impl: failed to load model common_init_from_params: failed to load model 'DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2.gguf'
srv load_model: failed to load model, 'DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2.gguf'

X-AI-GT

29 days ago

Thank you
You have 500GB of memory, why not just try the official version instead of the low precision GGUF version! I envy you for having 500GB of memory, hahaha, I only have 32GB of memory! Dancing on the road of collapse every day!

fususu

29 days ago

I tried on a Ubuntu Linux with 500 GB Ram but I obtain:
llama-cli -m DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2.gguf -cnv

Loading model... -llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'deepseek4'
llama_model_load_from_file_impl: failed to load model
common_fit_params: encountered an error while trying to fit params to free device memory: failed to load model \llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'deepseek4'
llama_model_load_from_file_impl: failed to load model common_init_from_params: failed to load model 'DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2.gguf'
srv load_model: failed to load model, 'DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2.gguf'

I figured it out and ran on my gx10 128vram here https://github.com/phuongncn/llama.cpp-gx10-dgx-sparks-deepseekv4

thirteenbit

25 days ago

Just lurking around but I see that README.md is empty.

This is the repository for this fork of llama.cpp that should work on CPU and Metal (Apple devices): https://github.com/antirez/llama.cpp-deepseek-v4-flash/

This model will not work in mainline llama.cpp as there's no support for the DeepSeek model architecture in mainline yet.

There's one active pull request there but it's not yet complete: https://github.com/ggml-org/llama.cpp/pull/22607

vagrillo

16 days ago

To run this models you need Antirez Inference called "DwarfStar 4". https://github.com/antirez/ds4

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