1.6 KiB
| name | description |
|---|---|
| dgx-spark-llama-cpp | Build llama.cpp with CUDA and serve models via an OpenAI-compatible API (Gemma 4 31B IT as example) — on NVIDIA DGX Spark. Use when setting up llama-cpp on Spark hardware. |
Run models with llama.cpp on DGX Spark
Build llama.cpp with CUDA and serve models via an OpenAI-compatible API (Gemma 4 31B IT as example)
llama.cpp is a lightweight C/C++ inference stack for large language models. You build it with CUDA so tensor work runs on the DGX Spark GB10 GPU, then load GGUF weights and expose chat through llama-server’s OpenAI-compatible HTTP API.
This playbook walks through that stack end to end. As the model example, it uses Gemma 4 31B IT - a frontier reasoning model built by Google DeepMind that llama.cpp supports, with strengths in coding, agentic workflows, and fine-tuning. The instructions download its F16 GGUF from Hugging Face. The same build and server steps apply to other GGUFs (including other sizes in the support matrix below).
Outcome: You will build llama.cpp with CUDA for GB10, download a Gemma 4 31B IT model checkpoint, and run llama-server with GPU offload. You get:
- Local inference through llama.cpp (no separate Python inference framework required)
- An OpenAI-compatible
/v1/chat/completionsendpoint for tools and apps - A concrete validation that Gemma 4 31B IT runs on this stack on DGX Spark
Full playbook: /home/runner/work/dgx-spark-playbooks/dgx-spark-playbooks/nvidia/llama-cpp/README.md