Cloudflare R2 and MosaicML enable training LLMs on any compute, anywhere in the world, with zero switching costs

This post introduces Cloudflare R2 as a solution for storing large datasets and model checkpoints for AI model training, specifically highlighting its zero-egress pricing model. It demonstrates how R2, when combined with MosaicML's tools (StreamingDataset and Composer), enables flexible and cost-effective training of large language models across multiple cloud providers without incurring prohibitive data transfer fees. This significantly enhances the utility of R2 beyond traditional caching by enabling it as a foundational storage layer for computationally intensive AI workloads.