Modal vs Runcrate

Run Python functions on NVIDIA GPUs without provisioning instances; cold starts in seconds

Pay for actual GPU runtime at sub-minute granularity, with scale-to-zero by default

Define environments in code, with automatic image building and caching

From T4 and L4 through A100, L40S, H100, H200 and B200

Token-billed API calls and GPU hours draw on one credit balance with a single invoice, auto-recharge, and credits that do not expire

Chat, image, video, text-to-speech, speech-to-text and embedding models served behind OpenAI-compatible REST endpoints, so existing clients switch by changing the base URL

Bare-metal instances with SSH, Docker and custom images, provisioned in about 60 seconds

An unauthenticated endpoint publishes the live GPU rate card, refreshed every few minutes

Reserved bare-metal from 16 to 128+ nodes with NVLink fabric and managed Slurm job submission

Python and TypeScript SDKs, a Vercel AI SDK provider, a CLI for instance and volume management, and an MCP server for controlling the platform from AI assistants