Files
openclaw/docs/plugins/reference/llama-cpp.md
T
Onur Solmaz c2de3206d4 feat(llama-cpp): support external llama-server
* feat(llama-cpp): add external server provider

* feat(llama-cpp): document external server setup

* refactor(llama-cpp): harden external provider boundaries

* fix(llama-cpp): support external structured output

* fix(llama-cpp): isolate replacement endpoint credentials

* test(llama-cpp): register external live shard

* fix(llama-cpp): preserve explicit endpoint authorization

* fix(llama-cpp): clear disabled inline credentials

* fix(llama-cpp): preserve external local service configs

* test(llama-cpp): cover retained external configs

* test(llama-cpp): cover authorization precedence
2026-08-19 17:32:00 +03:00

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Markdown

---
summary: "Managed and external llama.cpp servers for GGUF chat and embeddings."
read_when:
- You are installing, configuring, or auditing the llama-cpp plugin
title: "Llama Cpp plugin"
---
# Llama Cpp plugin
Managed and external llama.cpp servers for GGUF chat and embeddings.
## Distribution
- Package: `@openclaw/llama-cpp-provider`
- Install route: npm; ClawHub
## Surface
providers: `llama-cpp`, `llama-server`; contracts: `embeddingProviders`
<!-- openclaw-plugin-reference:manual-start -->
## Default text model
During interactive setup, OpenClaw installs a pinned, verified `llama-server`
and offers Gemma 4 E4B IT Q4_K_M as an approximately 5.0 GB download. The model
offer requires at least 16 GiB of total RAM. Existing cached models are still
detected on smaller machines.
To use another model, set `params.modelPath` to any custom GGUF. Custom models
are not subject to the bundled-download RAM requirement. On machines below the
requirement, you can also run a smaller model through Ollama or LM Studio, or
choose a cloud provider.
<!-- openclaw-plugin-reference:manual-end -->
## Related docs
- [llama-server](/providers/llama-server)
- [llama-cpp](/plugins/llama-cpp)