CoreWeave adds cross-region writes and an archive tier to its AI object storage
Cross-region write acceleration and the Archive tier are now live, cutting dataset copies for training; all performance figures are vendor-stated.
CoreWeave announced in an official blog post dated September 16 that two new capabilities in its AI Object Storage are now available: cross-region write acceleration and a new Archive storage class.
Cross-region write acceleration lets a training job write to a bucket in a remote region at local latency, reducing the extra dataset copies teams keep near their GPUs. The Archive class holds data such as checkpoints that is expected to be read rarely, instead of deleting it.
The post also describes its LOTA local caching component, saying a leading frontier model provider runs it across more than 15,000 GPUs and 20 PB of cache, with p99 read latency on cache hits more than 8x lower than reading from the bucket. These figures are vendor-stated and not independently tested.