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MatrixHub

Ask DeepWiki

MatrixHub is an open-source, self-hosted AI model registry engineered for large-scale enterprise inference. It serves as a drop-in private replacement for Hugging Face, purpose-built to accelerate vLLM and SGLang workloads.

๐Ÿ’ก Why MatrixHub?

MatrixHub streamlines the transition from public model hubs to production-grade infrastructure:

  • Zero-Wait Distribution: Eliminate bandwidth bottlenecks with a "Pull-once, serve-all" cache, enabling 10Gbps+ speeds across 100+ GPU nodes simultaneously.
  • Air-Gapped Delivery: Securely ferry models into isolated networks while maintaining a native HF_ENDPOINT experience for researchersโ€”no internet required.
  • Private AI model Registry: Centralize fine-tuned weights with Tag locking and CI/CD integration to guarantee absolute consistency from development to production.
  • Global Multi-Region Sync: Automate asynchronous, resumable replication between data centers for high availability and low-latency local access.

๐Ÿ› ๏ธ Core Features

๐Ÿš€ High-Performance Distribution

  • Transparent HF Proxy: Switch to private hosting with zero code changes by simply redirecting your endpoint.
  • On-Demand Caching: Automatically localizes public models upon the first request to slash redundant traffic.
  • Inference Native: Native support for P2P distribution, OCI artifacts, and NetLoader for direct-to-GPU weight streaming.

๐Ÿ›ก๏ธ Enterprise Governance & Security

  • RBAC & Multi-Tenancy: Project-based isolation with granular permissions and seamless LDAP/SSO integration.
  • Audit & Compliance: Full traceability with comprehensive logs for every upload, download, and configuration change.
  • Integrity Protection: Built-in malware scanning and content signing to ensure models remain untampered.

๐ŸŒ Scalable Infrastructure

  • Storage Agnostic: Compatible with local file systems, NFS, and S3-compatible backends (MinIO, AWS, etc.).
  • Reliable Replication: Policy-driven, chunked transfers ensure data consistency even over unstable global networks.
  • Cloud-Native Design: Optimized for Kubernetes with official Helm charts and horizontal scaling capabilities.

๐Ÿš€ Quick Start

Docker Compose Deployment

Use Docker Compose with the provided configuration files:

  • website/static/deploy/docker/docker-compose.yaml
  • website/static/deploy/docker/config.yaml

Make sure docker-compose.yaml and config.yaml are in the same folder, then start the service:

docker compose -f docker-compose.yaml up -d

Default service endpoint:

http://127.0.0.1:3001

Helm (Kubernetes) Deployment

MatrixHub provides two Helm installation methods โ€” from a local chart or from the OCI registry.

Set the install target first (used in all commands below):

export CHART_VERSION=<chart-version>  
export NAMESPACE=matrixhub

Option A: Install from Local Chart

helm install matrixhub ./deploy/charts/matrixhub \
  --namespace ${NAMESPACE} --create-namespace

Option B: Install from OCI Registry

Charts are published to GitHub Container Registry (ghcr.io) as OCI artifacts.

helm install matrixhub oci://ghcr.io/matrixhub-ai/matrixhub \
  --version ${CHART_VERSION} \
  --namespace ${NAMESPACE} --create-namespace

Expose the Service

Expose it via NodePort:

helm install matrixhub ./deploy/charts/matrixhub \
  --namespace ${NAMESPACE} --create-namespace \
  --set apiserver.service.type=NodePort
# or with OCI:
helm install matrixhub oci://ghcr.io/matrixhub-ai/matrixhub \
  --version ${CHART_VERSION} \
  --namespace ${NAMESPACE} --create-namespace \
  --set apiserver.service.type=NodePort

Persistent Storage (PVC)

MatrixHub uses PersistentVolumeClaims to persist data. Currently only PVC is supported as the storage backend; S3-compatible storage will be supported in a future release.

By default, the chart creates the following PVCs:

PVC Mount Path Default Size Purpose
<release>-apiserver-data /data/matrixhub 50Gi Model artifacts & cache
<release>-mysql-pv-claim /var/lib/mysql 8Gi Built-in MySQL data (only when global.storage.apiserver.builtIn=true, which is the default)

Customize storage class and size:

helm install matrixhub oci://ghcr.io/matrixhub-ai/matrixhub \
  --version ${CHART_VERSION} \
  --namespace ${NAMESPACE} --create-namespace \
  --set apiserver.storage.mode=pvc \
  --set apiserver.storage.pvc.size=50Gi \
  --set mysql.persistence.size=20Gi

Use an existing PVC:

helm install matrixhub oci://ghcr.io/matrixhub-ai/matrixhub \
  --version ${CHART_VERSION} \
  --namespace ${NAMESPACE} --create-namespace \
  --set apiserver.storage.pvc.existingClaim=my-existing-pvc

๐Ÿ“š Docs

Community, discussion, contribution, and support

Slack is our primary channel for community discussion, contribution coordination, and support. You can reach the maintainers and community at:

About

An Open-source, self-hosted AI model hub with Hugging Face compatibility, accelerating vLLM/SGLang performance.

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