AWS First Steps
Region expansion

Amazon EC2 P6-B300 instances now available in the AWS Asia Pacific (Jakarta) Region

Amazon EC2 introduces P6-B300 instances with 8xNVIDIA Blackwell Ultra GPUs and 2.1TB GPU memory, enhancing training and deployment of large-scale foundation models.

Amazon EC2 P6-B300 instances are now available in the Asia Pacific (Jakarta) region, featuring 8xNVIDIA Blackwell Ultra GPUs, 2.1TB high-bandwidth GPU memory, 6.4 Tbps EFA networking, 300 Gbps dedicated ENA throughput, and 4 TB system memory. With double the network bandwidth, 1.5x GPU memory, and 1.5x GPU TFLOPS (FP4, non-sparse) versus P6-B200 instances, P6-B300 is ideal for training and deploying large transformer-based models, including LLMs. Currently available as p6-b300.48xlarge in US West (Oregon), AWS GovCloud (US-East), US East (N. Virginia), Asia Pacific (Hyderabad, Jakarta, Seoul), and South America (Sao Paulo) regions. See the Amazon EC2 P6 instances page for details.

Why it matters

Amazon EC2 P6-B300 instances provide high-performance computing resources tailored for training and deploying large-scale foundation models and LLMs, offering users more efficient processing for AI workloads.

Read the original AWS announcement

Related articles and terms

GPU-Based Machine Learning Training with AWS Batch - Cost-Efficient Large-Scale TrainingRun GPU training with your existing Docker containers, and cut costs by up to 90% using Spot Instances and checkpointing. Includes guidance on when to choose Batch over SageMaker.Amazon Elastic Inference[Discontinued] Service that attached fractional GPU accelerators to EC2 and SageMaker for inference. Inferentia (Inf1 / Inf2), GPU instances, and SageMaker AI inference are the replacementsAmazon EC2A cloud-based virtual server service from AWS that lets you choose from hundreds of instance types and launch servers in minutesThe Layered Architecture of AWS AI/ML Services - Flexibility Through the Three Tiers of SageMaker, Bedrock, and API ServicesThis article organizes AWS AI/ML services into three layers - SageMaker (full control), Bedrock (managed generative AI), and Rekognition/Comprehend/etc. (API-based) - and explains AWS's flexibility through comparisons with GCP Vertex AI and Azure OpenAI Service, including custom silicon integration.Amazon SageMakerA fully managed platform for building, training, and deploying machine learning models end-to-end, significantly boosting productivity for data scientists and ML engineers