Baseten

AI Infrastructure

A platform for deploying and serving machine-learning models in production, with autoscaling, fast cold starts, and GPU infrastructure managed for you.

Overview

Baseten handles the unglamorous middle of running models: taking a model — open-weight, fine-tuned, or custom — and serving it as a reliable, autoscaling production endpoint without you managing GPU clusters. Its Truss packaging format and engineering focus on cold-start latency and scaling make it a strong fit when you need dedicated model serving rather than a shared API. For enterprises running their own or fine-tuned models, it removes most of the MLOps burden. If you only call hosted frontier APIs, you may not need it at all.

Pros & Cons

Pros

  • Production model serving without managing GPUs
  • Autoscaling with fast cold starts
  • Works with open, fine-tuned, and custom models
  • Removes most MLOps overhead

Cons

  • Unnecessary if you only use hosted frontier APIs
  • Compute-based cost grows with traffic
  • Still requires model and evaluation expertise

Workflows that use Baseten

Get a new AI workflow each week — many feature Baseten and other tools in this category.