NVIDIA and AWS Collaborate to Bring AI to Production at Scale

NVIDIA and AWS have collaborated to bring AI to production at scale, addressing constraints such as low-latency inference, fast vector search, and strong GPU price-performance. The NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs power new Amazon EC2 G7 instances, delivering up to 4.6x AI inference performance and up to 2.1x graphics performance compared to G6 instances. The NVIDIA cuVS library accelerates the retrieval layer by making GPU-powered vector indexing the default in OpenSearch Serverless, resulting in vector indexing up to 10x faster at a quarter of the cost. This collaboration provides enterprises with practical paths to deploy AI at production scale, enabling lower-latency inference and faster vector search.

⚡ Key Takeaways

• Amazon EC2 G7 instances deliver up to 4.6x AI inference performance and up to 2.1x graphics performance compared to G6 instances.
• The NVIDIA cuVS library makes GPU-accelerated vector indexing the default in OpenSearch Serverless, resulting in vector indexing up to 10x faster at a quarter of the cost.
• G7 instances support up to eight GPUs, 256GB of total GPU memory, 700 Gbps of EFA-enabled networking, and up to 7.6TB of local NVMe SSD storage.
• The NVIDIA cuVS library enables GPU-powered vector search, making it a standard AWS capability for teams building retrieval-augmented generation, semantic search, recommendation systems, and agentic AI applications.
• AWS has achieved NVIDIA Exemplar Cloud status for NVIDIA GB300, ensuring peak optimized performance for training workloads.

🔧 Tools & Libraries

This collaboration between NVIDIA and AWS provides enterprises with the infrastructure and tools needed to deploy AI at production scale, enabling faster and more efficient AI workloads. By leveraging NVIDIA's GPU technology and AWS's cloud infrastructure, businesses can accelerate their AI adoption and improve their competitiveness.

✅ Practical Steps

1. Deploy Amazon EC2 G7 instances to leverage NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs for AI inference, graphics, and data analytics workloads.
2. Use the NVIDIA cuVS library to accelerate vector search in OpenSearch Serverless, enabling faster and more efficient retrieval-augmented generation and semantic search applications.
3. Take advantage of AWS's NVIDIA Exemplar Cloud status for NVIDIA GB300 to ensure peak optimized performance for training workloads.

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