Baseten
AI InfrastructureA 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
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