Add GPUStack to LLM Deployment

README.md

@@ -286,6 +286,7 @@ If you're interested in the field of LLM, you may find the above list of milesto
 - [AI Gateway](https://github.com/Portkey-AI/gateway) — Gateway streamlines requests to 100+ open & closed source models with a unified API. It is also production-ready with support for caching, fallbacks, retries, timeouts, loadbalancing, and can be edge-deployed for minimum latency.
 - [talkd.ai dialog](https://github.com/talkdai/dialog) - Simple API for deploying any RAG or LLM that you want adding plugins.
 - [Wllama](https://github.com/ngxson/wllama) - WebAssembly binding for llama.cpp - Enabling in-browser LLM inference
+- [GPUStack](https://github.com/gpustack/gpustack) - An open-source GPU cluster manager for running LLMs
 
 ## LLM Applications
 - [AdalFlow](https://github.com/SylphAI-Inc/AdalFlow) - AdalFlow: The PyTorch library for LLM applications.