Baseten

What is Baseten?

Baseten is a platform for deploying machine-learning models as production APIs without managing servers. You bring a Python model or a container, and Baseten builds it, serves it on autoscaling GPUs, and gives you an endpoint with logging and monitoring. It supports both inference and, more unusually, long-running asynchronous jobs such as video generation pipelines. The differentiator is that it handles the deployment plumbing around custom models - the part that usually needs a platform engineer - while letting you keep the model code as written.

Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.

Key features

• Deploy custom Python models or container images as APIs
• Autoscaling GPU endpoints that scale to zero when idle
• Async pipelines for long-running generation jobs
• Model caching and warm pools to cut cold starts
• Training and fine-tuning jobs on managed GPUs
• Logs, metrics and versioned rollbacks per model

Pros & cons

Strengths

• Keeps your own model code instead of forcing a format
• Handles autoscaling and deployment work for you
• Async job support suits video and batch workloads

Watch out for

• You need real ML engineering skill to use it well
• Costs climb quickly on always-on GPU endpoints
• Less useful if you only need standard hosted models

Best for & use cases

custom model deployment, fine-tuned endpoints, video pipelines, autoscaling inference

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