Deploy and manage large language models on Kubernetes — no YAML required.

AI Runway gives you a web UI and a unified Kubernetes CRD (ModelDeployment) to deploy models across multiple inference providers. Browse HuggingFace, pick a model, click deploy.

• 🚀 One-Click Deploy — Browse models, check GPU fit, and deploy from the UI
• 🎯 Unified CRD — Single ModelDeployment API across all providers
• 🔧 Multiple Engines — vLLM, SGLang, TensorRT-LLM, llama.cpp
• 📈 Live Monitoring — Real-time status, logs, and Prometheus metrics
• 💰 Cost Estimation — GPU pricing and capacity guidance
• 🌐 Gateway API Integration — Unified inference endpoint via Gateway API Inference Extension with auto-detected setup
• 🔌 Headlamp Plugin — Full-featured Headlamp dashboard plugin

• Kubernetes cluster with kubectl configured
• helm CLI installed
• GPU nodes with NVIDIA drivers (KAITO also supports CPU-only)

Download the latest release and run:

./airunway

Open http://localhost:3001

macOS: Remove quarantine if needed: xattr -dr com.apple.quarantine airunway

# Install CRDs and controller (required)
kubectl apply -f https://raw.githubusercontent.com/kaito-project/airunway/main/deploy/controller.yaml

# Install dashboard UI (optional)
kubectl apply -f https://raw.githubusercontent.com/kaito-project/airunway/main/deploy/dashboard.yaml
kubectl port-forward -n airunway-system svc/airunway 3001:80

Open http://localhost:3001 — see deployment docs for more options.

1. Install a provider shim — Apply one or more provider shims to register providers with AI Runway. See Supported Providers for available options.
2. Install the provider — Go to the Installation page and install the upstream provider via Helm
3. Connect HuggingFace — Sign in via Settings → HuggingFace (optional for non-gated models)
4. Deploy a model — Browse the catalog, pick a model, configure, and deploy
5. Monitor — Track status, stream logs, and view metrics on the Deployments page

Deployed models expose an OpenAI-compatible API:

kubectl port-forward svc/<deployment-name> 8000:8000 -n <namespace>
curl http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model": "<model-name>", "messages": [{"role": "user", "content": "Hello!"}]}'

apiVersion: airunway.ai/v1alpha1
kind: ModelDeployment
metadata:
  name: my-model
spec:
  model:
    id: "Qwen/Qwen3-0.6B"

The controller automatically selects the best engine and provider, creates provider-specific resources, and reports unified status. See CRD Reference for details.

See CONTRIBUTING.md for development setup. We also accept AI-assisted prompt requests.