Baseten combines model routing, isolated agent environments, and serverless training
Prepared by Sintelligent with the help of SI. Published in SI: . Updated: .
Model training, model calls, and agent execution can be combined in one platform instead of assembled from separate services.
According to Baseten's description, Grid selects a model for a coding task within the Baseten platform. Sandboxes have moved from private to public preview: the environments are stateful, can pause and resume, are isolated at the virtual-machine level, and scale to thousands of instances in seconds. Colocating them with inference should reduce latency between agent execution and model calls. Serverless Loops adds supervised fine-tuning and reinforcement learning for open-weight models without infrastructure management; the customer retains ownership of the trained model weights.
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