Vast.ai is a GPU rental marketplace where developers and AI teams rent compute for training, fine-tuning, inference and rendering. Prices are set by supply and demand across more than 20,000 GPUs in over 40 data centers, with 68-plus GPU types and per-second billing. Users add as little as $5 in credit, search by model, VRAM, price and availability, and deploy through the console, CLI, Python SDK or REST API. The service is SOC 2 certified.
Machine learning engineers, startups, researchers and independent developers who want GPU access without long contracts are the main audience. Teams scaling consumer AI apps use it to cut infrastructure costs, and one featured case study cites savings of over 60 percent. Researchers fine-tune models, data teams run batch jobs, and creative developers render graphics. Because provisioning is API-native, builders of autonomous agents can also script how compute is found and launched, and organizations with hardware can list it for others to rent.
Three deployment modes cover different needs. GPU Cloud gives full control over on-demand instances, Serverless deploys models as endpoints that autoscale to zero and bill only for compute time, and Clusters provide dedicated multi-node setups with InfiniBand networking for large training runs. A model library offers ready templates such as Qwen3.8 27B, Kimi K3 and MiniMax H3. Common workloads include AI text generation, image and video generation, audio-to-text transcription, fine-tuning, virtual computing and GPU programming. Installing the CLI takes one command, and the Python SDK launches instances in a few lines of code.
