Instructions to use wickgraveyard/deepseek-r1-70b-nvfp4-blackwell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use wickgraveyard/deepseek-r1-70b-nvfp4-blackwell with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="wickgraveyard/deepseek-r1-70b-nvfp4-blackwell",
	filename="deepseek-r1-70b-nvfp4-blackwell.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 wickgraveyard/deepseek-r1-70b-nvfp4-blackwell 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 wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4
# Run inference directly in the terminal:
llama cli -hf wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4
# Run inference directly in the terminal:
llama cli -hf wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4

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 wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4
# Run inference directly in the terminal:
./llama-cli -hf wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4

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 wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4
# Run inference directly in the terminal:
./build/bin/llama-cli -hf wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4

Use Docker

docker model run hf.co/wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4

LM Studio
Jan
Ollama
How to use wickgraveyard/deepseek-r1-70b-nvfp4-blackwell with Ollama:
```
ollama run hf.co/wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4
```

Unsloth Studio

How to use wickgraveyard/deepseek-r1-70b-nvfp4-blackwell 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 wickgraveyard/deepseek-r1-70b-nvfp4-blackwell 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 wickgraveyard/deepseek-r1-70b-nvfp4-blackwell to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for wickgraveyard/deepseek-r1-70b-nvfp4-blackwell to start chatting

Atomic Chat new
Docker Model Runner
How to use wickgraveyard/deepseek-r1-70b-nvfp4-blackwell with Docker Model Runner:
```
docker model run hf.co/wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4
```

Lemonade

How to use wickgraveyard/deepseek-r1-70b-nvfp4-blackwell with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull wickgraveyard/deepseek-r1-70b-nvfp4-blackwell:NVFP4

Run and chat with the model

lemonade run user.deepseek-r1-70b-nvfp4-blackwell-NVFP4

List all available models

lemonade list

DeepSeek-R1-Distill-Llama-70B — NVFP4 Blackwell GGUF

NVFP4 quantized GGUF for NVIDIA Blackwell GPUs (DGX Spark / GB10).

Converted from unsloth/DeepSeek-R1-Distill-Llama-70B-GGUF Q4_K_M → NVFP4 using llama.cpp's --tensor-type-file method.

Performance

Metric	Q4_K_M	NVFP4
Size	40 GB	37 GB
Generation	~2.6 tok/s	~5.7 tok/s
Prompt eval	~115 tok/s	~93 tok/s

NVFP4 is ~2.2x faster than Q4_K_M on Blackwell hardware.

Usage

ollama create deepseek-r1:70b-nvfp4 -f - << 'EOF'
FROM ./deepseek-r1-70b-nvfp4-blackwell.gguf
PARAMETER temperature 0.7
PARAMETER num_ctx 32768
EOF

Hardware Requirements

NVIDIA Blackwell GPU (sm_120/sm_121) — DGX Spark, RTX PRO 6000 Blackwell, RTX 5090
Ollama 0.30.11+ with NVFP4 support
~37 GB storage, ~37 GB RAM/VRAM at load
Fits comfortably in DGX Spark (121 GB unified memory)

Downloads last month: 292

GGUF

Model size

71B params

Architecture

llama

Hardware compatibility

4-bit

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