Vidman AI Platform
Overviews of Vidman AI itself: what the platform does, how it is put together, and how the pieces fit together.
Workspaces, API Keys, and Environments
Keys, workspaces, and environment boundaries are the operations layer nobody demos. How to issue, scope, rotate, and watch them before the first incident.
The Model Library: How We Pick What We Serve
A model library is a set of promises, not a list: how entries earn their place, why the rest are declined, and the pricing honesty behind each one.
Serverless, Adaptive, or Dedicated: Picking How Your Models Run
Three ways to serve a model on Vidman AI: pay-per-token serverless, Vidman AI Adaptive routing, and dedicated GPU endpoints. What each is for, and how to choose.
How Vidman AI Compares to Other AI Fine-Tuning Platforms
How Vidman AI compares for fine-tuning: 15+ training methods, 6 alignment objectives, per-second GPU billing, and weights you own.
What Vidman AI Adaptive Actually Decides
Vidman AI Adaptive routes every request to the best model for the task: what the router weighs, how the choice lands, and where its knowledge ends.
Browse other topics