Runcrate vs. Compute with Hivenet

Runcrate provides a consolidated account for AI teams and their agents to effortlessly access GPUs and inference capabilities. Users have the option to rent from a wide selection of GPU models, including H100, H200, A100, L40S, RTX 4090, and RTX PRO 6000, totaling over 20 choices available for hourly rental, all supporting SSH, Jupyter, and VS Code directly through their web browsers. The launch process is incredibly swift, taking around four minutes, and users are billed only for the duration their GPUs are in use, with most transactions calculated by the second. For inference needs, clients can tap into an extensive library of over 200 open models, such as DeepSeek, Qwen, Llama, Kimi, FLUX, and Whisper, all accessible via a single OpenAI-compatible API, ensuring seamless integration with existing applications. The pricing model is based on various usage metrics, including tokens, images, or seconds, while ample storage options are available to retain datasets and checkpoints across multiple instances. Reserved clusters can accommodate more than eight GPUs and offer monthly service plans for extended use. Specifically designed for agents, users are able to connect tools like Claude Code, Codex, or Cursor to the Runcrate MCP server with a single command and can log in through their browser without requiring key inputs. Once connected, agents can efficiently launch a GPU, execute their commands, and terminate the session when complete. Furthermore, the platform includes a command-line interface that can be installed easily with a simple command, alongside SDKs available for both Python and TypeScript, which significantly enhance development flexibility and user experience. Overall, Runcrate stands out as a versatile and user-friendly solution for AI teams seeking powerful GPU capabilities.

Hivenet Compute gives you on-demand RTX 5090 and RTX Pro 6000 GPUs, plus vCPU instances, billed per second while they run. Hivenet owns and operates the infrastructure, with data centres in France, the UAE and the US, so EU teams can keep workloads and data in Europe. Use it for training and fine-tuning, inference, notebooks, rendering and batch jobs. Launch from ready-made templates in a few minutes, or automate everything through the public Compute API. If you'd rather not run the serving layer yourself, the Inference API gives you an OpenAI-compatible endpoint. Teams get organisations with role-based access, prepaid credits, and S3-compatible object storage alongside compute.