Instructions to use Preyazz/DeepSeek-V4-Flash-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Preyazz/DeepSeek-V4-Flash-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Preyazz/DeepSeek-V4-Flash-GGUF",
	filename="DeepSeek-V4-Flash-Q2_K.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Preyazz/DeepSeek-V4-Flash-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Preyazz/DeepSeek-V4-Flash-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Preyazz/DeepSeek-V4-Flash-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 Preyazz/DeepSeek-V4-Flash-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Preyazz/DeepSeek-V4-Flash-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 Preyazz/DeepSeek-V4-Flash-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Preyazz/DeepSeek-V4-Flash-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 Preyazz/DeepSeek-V4-Flash-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Preyazz/DeepSeek-V4-Flash-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Preyazz/DeepSeek-V4-Flash-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use Preyazz/DeepSeek-V4-Flash-GGUF with Ollama:
```
ollama run hf.co/Preyazz/DeepSeek-V4-Flash-GGUF:Q4_K_M
```

Unsloth Studio new

How to use Preyazz/DeepSeek-V4-Flash-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 Preyazz/DeepSeek-V4-Flash-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 Preyazz/DeepSeek-V4-Flash-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Preyazz/DeepSeek-V4-Flash-GGUF to start chatting

Docker Model Runner
How to use Preyazz/DeepSeek-V4-Flash-GGUF with Docker Model Runner:
```
docker model run hf.co/Preyazz/DeepSeek-V4-Flash-GGUF:Q4_K_M
```

Lemonade

How to use Preyazz/DeepSeek-V4-Flash-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Preyazz/DeepSeek-V4-Flash-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.DeepSeek-V4-Flash-GGUF-Q4_K_M

List all available models

lemonade list

DeepSeek-V4-Flash GGUF (community quants)

Quantized variants of deepseek-ai/DeepSeek-V4-Flash (284B params, 13B active per token).

Quants

Quant	Approx size	Recommended?
~~IQ1_S~~	~~~54 GB~~	Removed
~~IQ2_M~~	~~~87 GB~~	Removed
~~IQ3_XS~~	~~~109 GB~~	Removed
Q2_K	~96 GB
Q3_K_M	~125 GB
Q4_K_M	~161 GB

Provenance

All variants derived from Preyazz/DeepSeek-V4-Flash-Q8_0-GGUF, which is itself a lossless conversion of the original FP8 safetensors.

Compatibility

Requires llama.cpp built from PR #22378 (nisparks's wip/deepseek-v4-support branch) or later. The deepseek4 architecture is not yet in stable llama.cpp releases.

For Strix Halo / consumer ROCm: build with GGML_HIP_NO_VMM=ON (VMM=ON currently crashes on gfx1151 — see ROCm Issue #6146).

Downloads last month: 99,383

GGUF

Model size

284B params

Architecture

deepseek4

Hardware compatibility

2-bit

3-bit

4-bit

Inference Providers NEW

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

Model tree for Preyazz/DeepSeek-V4-Flash-GGUF

Base model

deepseek-ai/DeepSeek-V4-Flash

Quantized

Preyazz/DeepSeek-V4-Flash-Q8_0-GGUF

Quantized

(1)

this model