How to use from
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 DeepBeepMeep/3D:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DeepBeepMeep/3D:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf DeepBeepMeep/3D:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DeepBeepMeep/3D:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf DeepBeepMeep/3D:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf DeepBeepMeep/3D:Q4_K_M
Use Docker
docker model run hf.co/DeepBeepMeep/3D:Q4_K_M
Quick Links

You will find here all the 3D models used with WanGP (https://github.com/deepbeepmeep/Wan2GP) :

WanGP by DeepBeepMeep : The best Open Source Video Generative Models Accessible to the GPU Poor

WanGP supports the Wan (and derived models), Minimax H3, Hunyuan Video, Flux 1,2 & 3, Qwen, Z-Image and LTX-2, LTX Video models with:

Low VRAM requirements (as low as 6 GB of VRAM is sufficient for certain models) Support for old GPUs (RTX 10XX, 20xx, ...) Very Fast on the latest GPUs Easy to use Full Web based interface Auto download of the required model adapted to your specific architecture Tools integrated to facilitate Video Generation : Mask Editor, Prompt Enhancer, Temporal and Spatial Generation Loras Support to customize each model Queuing system : make your shopping list of videos to generate and come back later Discord Server to get Help from Other Users and show your Best Videos: https://discord.gg/g7efUW9jGV

Follow DeepBeepMeep on Twitter/X to get the Latest News: https://x.com/deepbeepmeep

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Architecture
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