Deep Infra vs Runcrate

OpenAI-compatible API for 100+ models including DeepSeek, Qwen, Llama 4, Claude, and Gemini families with autoscaling

B200 instances with SSH access spin up in about 10 seconds and bill hourly

Deploy your own Hugging Face models onto dedicated A100, H100, H200, B200, or B300 GPUs

Published per-GPU hourly rates for A100, H100, H200, B200, and B300 with competitive pricing

Runs on its own inference-optimized hardware in US-based data centers rather than rented capacity

Support for text generation, vision and OCR, embeddings and reranking, image, video and music generation, and speech recognition and synthesis

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