Chutes

Organizations running GPU-accelerated applications face significant operational overhead: maintaining GPU clusters, managing infrastructure scaling, dealing with idle compute capacity during off-peak hours, and paying for compute resources whether in use or not. Traditional GPU cloud providers charge by instance type and time, forcing users to over-provision to handle traffic spikes or accept poor performance. Teams spend engineering effort on DevOps rather than application development.

A decentralized approach distributes GPU workload execution across a network of independently-operated compute providers, where capacity dynamically adjusts to actual demand. Applications scale up automatically when demand increases and scale down when traffic drops, with billing tied directly to GPU runtime rather than reserved capacity. This eliminates idle compute charges and infrastructure management overhead.

Chutes implements this model through a development kit that lets users define GPU requirements declaratively (GPU count, VRAM, price limits), deploy applications as containerized FastAPI services, and expose individual functions as API endpoints. The platform handles node selection, instance scaling, GPU validation, and billing automatically.

Chutes is a development kit and CLI for the chutes.ai platform, enabling users to build Docker images, deploy FastAPI applications (chutes), and manage GPU-accelerated inference workloads. It provides tools for creating containerized applications with CUDA support, managing API keys, and scaling applications on a distributed GPU network with billing based on actual GPU usage.