Intel Gaudi 3 on AWS
Shares tags: deploy, hardware, inference cards
Configurable TPU slices optimized for low-latency inference, available now via Vertex AI and GKE.
Tags
Similar Tools
Other tools you might consider
overview
Google Cloud TPU v5e Pods are designed for medium to large-scale AI training and inference, focusing on generative AI and large language models. With advanced capabilities, they offer a unique blend of high throughput and low latency, ensuring your AI applications operate smoothly.
features
Each v5e Pod supports up to 256 interconnected chips, delivering unprecedented compute power exceeding 100 petaOps (INT8) and bandwidth over 400 Tb/s. With eight distinct VM configurations, users can seamlessly scale resources to fit their AI workloads.
use_cases
Google Cloud TPU v5e Pods are perfect for teams seeking to implement high-throughput, cost-effective AI solutions. Whether developing generative models, handling large datasets, or deploying complex AI applications, these Pods deliver the performance you need.
TPU v5e Pods are ideal for medium to large-scale AI workloads, particularly for generative AI applications and large language models, providing unmatched performance and scalability.
Getting started is easy! Simply sign in to your Google Cloud account, access Vertex AI or GKE, and configure your TPU resources to match your project requirements.
TPU v5e Pods offer up to 2x higher training and 2.5x higher inference performance per dollar compared to previous models, making them an exceptionally cost-effective choice for AI computing.