Overview
Baseten provides ML inference infrastructure for deploying models to production. The platform focuses on reliability, performance, and developer experience for teams running ML inference at scale. Baseten offers both serverless and dedicated deployment options with enterprise features.
The platform uses Truss, an open-source tool for packaging ML models, making deployment standardized and reproducible. Baseten is designed for engineering teams that need production-grade ML infrastructure without building it themselves.
Key Features
**Truss**: Open-source model packaging**Auto-Scaling**: Serverless and dedicated options**Multi-Framework**: PyTorch, TensorFlow, JAX support**Monitoring**: Detailed observability**CI/CD**: Integrated deployment pipelines**Versioning**: Model version management**VPC Deployment**: Private deployment options**Enterprise Features**: SSO, audit logs, SLAsWhen to Use Baseten
Baseten is ideal for:
Production ML inference workloadsEngineering teams needing reliabilityCompanies requiring enterprise featuresMulti-model deploymentsOrganizations wanting open packaging (Truss)Teams scaling from prototype to productionPros
Production-ready infrastructureOpen-source Truss for packagingGood developer experienceEnterprise features availableMulti-framework supportStrong monitoring and observabilityGood documentationVPC deployment optionsCons
More expensive than some alternativesRequires technical setupSmaller than major cloud providersLimited model library (deploy your own)Overkill for simple inferenceLearning curve for TrussNewer platformVendor lock-in concernsPricing
**Free**: $30 credit monthly**Serverless**: Usage-based pricing**Dedicated**: Starting at $1,200/month**Enterprise**: Custom pricing