AWS shows how to tune SageMaker training for NVIDIA Blackwell

AWS has published a practical guide to configuring training jobs on Amazon SageMaker AI for NVIDIA Blackwell GPUs. The post focuses on how to select batch sizes and sequence lengths, choose precision formats for models from 1B to 64B parameters, and use activation checkpointing effectively.

The guidance is aimed at getting more out of Blackwell’s expanded memory and architecture on AWS. That matters because hardware upgrades only translate into better training economics when workloads are tuned for them.

For teams scaling model training, the post offers an infrastructure-level playbook rather than a high-level product announcement.