Baseten
ML model deployment platform. Deploy AI models with autoscaling and monitoring.
About Baseten
Baseten is a model deployment platform that helps ML teams deploy, serve, and monitor machine learning models in production. It handles infrastructure so teams can focus on models.
The platform supports deploying models from any framework including PyTorch, TensorFlow, and Hugging Face. It provides autoscaling, monitoring, and model versioning out of the box.
Baseten is designed for ML engineers and data scientists who need to move models from development to production quickly without managing infrastructure.
Key Features
- ✓Model Deployment:
- ✓Auto-Scaling:
- ✓GPU Infrastructure:
- ✓Model Monitoring:
- ✓A/B Testing:
- ✓Truss Framework:
Pricing
| Plan | Price | Key Features |
|---|---|---|
| Free | Free trial | Basic features with limited usage |
| Pro / Premium | Free trial | Full features, higher limits, priority support |
| Enterprise | Custom | SSO, admin controls, SLA, dedicated support |
Pros & Cons
✅ Pros
- ✅ Easy model deployment
- ✅ Good autoscaling
- ✅ Built-in monitoring
- ✅ Enterprise ready
⚠️ Cons
- ⚠️ Enterprise pricing
- ⚠️ Complex for simple models
- ⚠️ Limited free tier
Use Cases
Model Deployment
Deploy ML models to production with autoscaling and monitoring in minutes.
API Serving
Create scalable API endpoints for model inference with low latency.
Model Monitoring
Track model performance, latency, and usage in production.
MLOps
Streamline the ML deployment pipeline from development to production.
Alternatives
Frequently Asked Questions
What is Baseten?
Baseten is a platform for deploying and serving machine learning models in production with managed infrastructure, autoscaling, and monitoring.
What frameworks does Baseten support?
Baseten supports PyTorch, TensorFlow, scikit-learn, XGBoost, and models from Hugging Face and other popular frameworks.
Is Baseten open source?
Baseten is a managed platform with a free tier. The model serving runtime is open source as Truss.