Welcome to AIBrix, an open-source initiative designed to provide essential building blocks to construct scalable GenAI inference infrastructure. AIBrix delivers a cloud-native solution optimized for deploying, managing, and scaling large language model (LLM) inference, tailored specifically to enterprise needs.
| Documentation | Blog | White Paper | Twitter/X | Developer Slack |
The initial release includes the following key features:

To get started with AIBrix, clone this repository and follow the setup instructions in the documentation. Our comprehensive guide will help you configure and deploy your first LLM infrastructure seamlessly.
# Local Testing
git clone https://github.com/vllm-project/aibrix.git
cd aibrix
# Install nightly aibrix dependencies
kubectl apply -k config/dependency --server-side
# Install nightly AIBrix CRDs (separate from the operator so uninstalls don't wipe user CRs)
kubectl apply -k config/crd --server-side
# Install nightly aibrix components
kubectl apply -k config/default
Install stable distribution
# Install component dependencies
kubectl apply -f "https://github.com/vllm-project/aibrix/releases/download/v0.7.0/aibrix-dependency-v0.7.0.yaml" --server-side
# Install AIBrix CRDs (separate from the operator so uninstalls don't wipe user CRs)
kubectl apply -f "https://github.com/vllm-project/aibrix/releases/download/v0.7.0/aibrix-core-crds-v0.7.0.yaml" --server-side
# Install aibrix components
kubectl apply -f "https://github.com/vllm-project/aibrix/releases/download/v0.7.0/aibrix-core-v0.7.0.yaml"
For detailed documentation on installation, configuration, and usage, please visit our documentation page.
We welcome contributions from the community! Check out our contributing guidelines to see how you can make a difference.
Slack Channel: #aibrix
AIBrix is licensed under the Apache 2.0 License.
If you have any questions or encounter any issues, please submit an issue on our GitHub issues page.
Thank you for choosing AIBrix for your GenAI infrastructure needs!
$ claude mcp add aibrix \
-- python -m otcore.mcp_server <graph>