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Description

Runcrate offers AI teams and their agents a unified account to access GPUs and inference capabilities seamlessly. Users can rent various GPU models, including H100, H200, A100, L40S, RTX 4090, and RTX PRO 6000, with over 20 options available, for hourly use, featuring SSH, Jupyter, and VS Code directly in their browsers. A launch can be initiated in approximately four minutes, and users are only charged for running time, with most GPUs billing by the second. In terms of inference, clients can access more than 200 open models, such as DeepSeek, Qwen, Llama, Kimi, FLUX, and Whisper, through a single OpenAI-compatible API, ensuring compatibility with existing clients. Pricing is structured based on usage metrics like tokens, images, or seconds, while storage volumes allow for the retention of datasets and checkpoints across different instances. Reserved clusters can support over eight GPUs or provide month-long service options. Designed specifically for agents, users can connect tools like Claude Code, Codex, or Cursor to the Runcrate MCP server using a single command and sign in via their browser without needing to input any keys. Once connected, agents can easily launch a GPU, execute commands, and shut it down when finished. Additionally, the platform provides a command-line interface, which can be installed with a simple command, along with SDKs available for both Python and TypeScript to enhance development flexibility.

Description

Automated Optimization for AWS Savings Plans and Reserved Instances streamlines the entire process of planning, purchasing, and enhancing your cloud commitments portfolio. Eco facilitates the lifecycle management of reserved instances, crafting a cloud commitment portfolio that is both high in return on investment and low in risk, tailored to your current and future requirements. By pinpointing and liquidating unused capacity while acquiring suitable short-term, third-party reservations from the AWS Marketplace, Eco allows you to reap the benefits of long-term pricing without being tied down financially. This approach ensures that you achieve the highest possible return on investment from your cloud commitment purchases through thorough analysis, adjustments, and alignment of unutilized reserved instances and Savings Plans with resource demands. Additionally, Eco automates purchasing strategies for reserved instances throughout their lifecycle in the AWS Marketplace, guaranteeing that workloads are perpetually operating at the best pricing. Collaboration between Finance and DevOps teams is enhanced by providing full transparency into compute consumption and automating the selection of optimal reserved instances, ultimately leading to a more efficient cloud resource management process. With these capabilities, organizations can adapt more swiftly to changing needs while optimizing their cloud expenditure.