Autoscaling Large AI Models up to 5.1x Faster on Anyscale

Efficiency is crucial for AI applications, both in development and production. However, a common experience among AI practitioners is spending significant time waiting for instances to boot, containers to pull, and models to load. Anyscale has optimized scale-up speed across the entire stack, leading to up to 5.1x faster autoscaling for Meta-Llama-3-70B-Instruct on the Anyscale platform compared to running the same application using KubeRay on Amazon Elastic Kubernetes Service (EKS). Faster scale-up speeds benefit AI engineers and researchers by enabling quick iteration, avoiding idle time in development, and autoscaling to meet workloads' demands while avoiding idle resources in production. The Anyscale Platform provides a fully-managed Ray solution with tailored infrastructure for high performance, cost effectiveness, and fast model loading.