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vLLM

Serves language models with high throughput, efficient memory use, batching, and OpenAI-compatible APIs.

Install in ToolsView on GitHub ↗

What it provides

LLM servingGPUOpenAI API

Connect an HTTPS inference API. Model weights stay on CPU/GPU infrastructure and are never installed inside the 4 GB bot.

Connection requirements

A vLLM OpenAI-compatible server

Protocol
OpenAI-compatible REST
Endpoint
https://vllm.example.com
Authentication
Choose the mode required by your service
Open official setup guide ↗

Where to add it

Open Dashboard Tools, select a running OpenClaw or Hermes instance, then use the card’s Install or Connect action. External services may require an HTTPS endpoint and credentials; the dashboard shows those fields before anything is saved.

Related Models & routing

OllamaDownloads, manages, and serves a broad catalog of local language and vision models through a simple API.llama.cppRuns quantized language models efficiently across CPU, Metal, CUDA, Vulkan, and other hardware backends.LiteLLMNormalizes model providers behind OpenAI-compatible APIs with routing, budgets, guardrails, and logging.