Llama Cpp Plugin: Managed Local GGUF Chat and Embeddings

This page covers the Llama Cpp plugin for OpenClaw, a locally managed llama.cpp server for GGUF chat and embeddings. It details installation, default models, and memory requirements for developers and users.

Read this when

  • You are installing, configuring, or auditing the llama-cpp plugin

Llama Cpp plugin

A locally managed llama.cpp server that handles GGUF chat and embedding workloads.

Distribution

  • Package: @openclaw/llama-cpp-provider
  • Install route: npm; ClawHub

Surface

providers: llama-cpp; contracts: embeddingProviders

Default text model

When you go through interactive setup, OpenClaw pulls in a pinned, verified llama-server and presents Gemma 4 E4B IT Q4_K_M as an approximately 5.0 GB download. That model option needs a minimum of 16 GiB of total RAM. Even on machines with less memory, any previously cached models are still recognized.

If you want a different model, point params.modelPath at any custom GGUF file. Those custom models bypass the RAM constraint tied to the bundled download. For systems that fall short of the requirement, a smaller model can be run through Ollama or LM Studio, or you can opt for a cloud provider.

144 words · updated Aug 17, 2026