Nvidia Deepens AWS Partnership, Embedding Tech in Amazon's Custom AI Chips
Shares rise as the strategic alliance ensures Nvidia's critical NVLink technology will be integrated into AWS's next-generation Trainium and Graviton processors.
Nvidia Corp. has further cemented its indispensable role in the artificial intelligence arms race, forging a deeper alliance with Amazon Web Services that will see its proprietary technology embedded directly into Amazon’s next generation of custom-built AI chips.
In a move that underscores the complex blend of competition and collaboration defining the AI hardware landscape, the two technology giants announced the expanded partnership Tuesday at the annual AWS re:Invent conference. The deal will integrate Nvidia’s high-speed NVLink interconnect technology into AWS’s forthcoming Trainium4 AI training chips and Graviton CPUs. Shares of Nvidia rose nearly 1% in morning trading to $181.61, pushing its market capitalization to a formidable $4.3 trillion.
The strategic pact highlights a crucial dynamic in the generative AI era: even as cloud titans like Amazon develop their own silicon to reduce costs and dependence on Nvidia's dominant GPUs, they continue to rely on the chipmaker's foundational technology to achieve elite performance. Nvidia and AWS announced the collaboration as a way to jointly “accelerate generative AI innovation.”
For Nvidia, the arrangement provides a powerful hedge against the rise of in-house chip development by its largest customers. By licensing its NVLink technology, which allows for ultra-fast communication between processors, Nvidia ensures it remains a critical component supplier inside AWS's data centers, generating revenue and locking in its architecture regardless of whether the primary processing is done by an Nvidia GPU or an Amazon-designed chip.
This move is seen by analysts as a strategic masterstroke, shifting Nvidia’s role from purely a chip vendor to an essential enabler of the entire AI ecosystem. While hyperscalers are investing billions to create alternatives to Nvidia’s coveted GPUs, they are finding it difficult to replicate the performance of Nvidia's full-stack solution, which includes its CUDA software platform and advanced interconnects.
The announcement comes as AWS is aggressively pushing its own silicon. The company also unveiled its new Trainium2 chip, which it claims offers significantly better performance and cost-efficiency for training AI models compared to its predecessor. While this presents long-term competition, the integration of Nvidia's NVLink into the next generation of these chips suggests a pragmatic, best-of-both-worlds approach from Amazon.
Wall Street has remained overwhelmingly bullish on Nvidia's prospects despite the competitive noise. The company holds a strong consensus rating from analysts, with 60 of 64 analysts tracked by major platforms rating the stock a "buy" or "strong buy," carrying an average price target of over $250. Investors have been rewarded with a stock that has soared from a 52-week low of $86.61.
Beyond the custom chip integration, the expanded partnership also involves AWS offering massive instances of Nvidia's latest and most powerful GPUs. AWS announced it will build “AI Factories” featuring Nvidia's Blackwell GB200 NVL72 systems, which combine 72 Blackwell GPUs with Grace CPUs connected by NVLink. These systems are designed for the most demanding large language model (LLM) inference and training workloads.
This dual strategy—embedding its technology in third-party chips while simultaneously selling its own state-of-the-art GPU platforms—positions Nvidia to capture value across the entire AI infrastructure stack. It effectively allows the company to profit from both the build-out of custom cloud silicon and the continued demand for its own market-leading processors.
The collaboration signals a maturing market where "co-opetition" is becoming the norm. For AWS, leveraging Nvidia's interconnects allows it to focus its resources on optimizing its chip architecture for specific workloads prevalent in its cloud, without needing to reinvent the highly complex and costly technology that allows processors to communicate at scale. As reported by SiliconAngle, this approach helps AWS meet the growing demand for sovereign AI capabilities and on-premises deployments.
As the industry pushes the boundaries of AI, the ability to process and move massive datasets with minimal latency is paramount. Nvidia’s NVLink has become a critical piece of that puzzle, and its integration into AWS’s roadmap ensures that, for the foreseeable future, all roads in the AI data center continue to lead, in some way, through Nvidia.