NVIDIA (NVDA), AWS (AMZN) Partner to Boost Production-Scale AI with Blackwell-Powered Instances

Yahoo Finance · 2026-06-26

NVIDIA (NVDA), AWS (AMZN) Partner to Boost Production-Scale AI with Blackwell-Powered Instances Maham Fatima Fri, June 26, 2026 at 4:04 AM EDT 1 min read NVDA AMZN NVIDIA Corporation (NASDAQ: NVDA ) is one of the best stocks for beginners to buy now . On June 23, NVIDIA and AWS partnered to simplify production-scale AI by enhancing compute and retrieval layers. The new Amazon EC2 G7 instances, powered by NVIDIA Blackwell GPUs, deliver significantly faster AI inference and graphics performance, allowing enterprises to right-size infrastructure without operational overhead. Data retrieval is also improved as AWS now uses NVIDIA cuVS to make GPU-accelerated vector search the default in Amazon OpenSearch Serverless. This change makes building billion-scale vector databases up to 10x faster and more cost-effective, streamlining the path from raw data to production-ready AI applications. Furthermore, AWS has earned NVIDIA Corporation (NASDAQ:NVDA) Exemplar Cloud status for the GB300, confirming its infrastructure meets the highest benchmarks for large-scale AI training. Together, these upgrades provide a standardized, high-performance stack that allows teams to scale AI projects more efficiently while reducing management complexity. NVIDIA Corporation (NASDAQ:NVDA) is a fabless semiconductor and AI computing company that designs GPUs, AI accelerators, Application Programming Interfaces, and system-on-a-chip units. Through its CUDA ecosystem, the company enables industries ranging from autonomous vehicles to scientific research by advancing AI, accelerated computing, and data center infrastructure. While we acknowledge the potential of NVDA as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you're looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the best short-term AI stock . READ NEXT: 33 Stocks That Should Double in 3 Years and Cathie Wood 2026 Portfolio: 10 Best Stocks to Buy . Disclosure: None. Follow Insider Monkey on Google News .

AI 시장 분석

NVDA and AWS announced a collaboration to standardize NVIDIA Blackwell GPU–based Amazon EC2 G7 instances and GPU-accelerated vector search (cuVS) as the default in OpenSearch Serverless. AWS obtained NVIDIA Exemplar Cloud status for GB300, validating the performance and compatibility of large-scale AI training and inference stacks. This enables enterprises to deploy billion-scale vector DBs up to 10x faster and more cost-effectively while improving inference speed and graphics performance and reducing infrastructure operations burden. As a result, demand for NVIDIA GPUs and the migration of AI workloads to the AWS cloud are expected to accelerate, exerting pressure on competitors, on-premises hardware, and smaller cloud providers.

상승 영향

Semiconductors (GPU) — Adoption of Blackwell in EC2 G7 will drive a surge in demand for high-performance GPUs, boosting revenue and ASPs for NVDA and other GPU designers/manufacturers.
Cloud Services (AWS) — By securing high-performance AI instances and Exemplar Cloud certification, AWS strengthens enterprise cloud migration and customer lock-in, supporting improved profitability.
AI Infrastructure & MLOps — Improvements in inference and vector search performance lower model deployment and operational costs, accelerating adoption of MLOps platforms and automation tools.
Vector databases & Search — With cuVS-based GPU-accelerated vector search becoming standard, the cost and speed competitiveness of building billion-scale vector DBs will improve markedly, increasing demand for related solutions.
Data Center Infrastructure (Networking, — Workload growth centered on high-performance GPUs raises demand for high-bandwidth networking, NVMe storage, and power/cooling solutions, benefiting related hardware suppliers.
Enterprise Software & SaaS — Reduced time and cost to develop AI applications will accelerate commercialization of SaaS and enterprise AI solutions, expanding demand for related software vendors.

하락 영향

Semiconductor competitors — A stronger NVIDIA-centric ecosystem could erode market share and price competitiveness for rivals in GPU-heavy markets.
On-premise servers & traditional hardwar — Widespread availability of standardized, high-performance AI instances in the cloud may reduce investment in private data centers and demand for on-premises hardware, depressing sales.
Small cloud providers & Managed Service — AWS standardizing a high-performance stack makes it difficult for smaller CSPs and MSPs to match performance and scale, risking customer churn and margin pressure.
Low-end GPU/CPU-based AI infrastructure — If GPU-accelerated vector search becomes the standard, solutions reliant on CPUs or low-spec GPUs will lose competitiveness, triggering replacement demand and revenue decline.

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