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Amazons AWS fires back at Nvidia with Graviton4 and Trainium3
Amazons AWS fires back at Nvidia with Graviton4 and Trainium3

Yahoo

time2 days ago

  • Business
  • Yahoo

Amazons AWS fires back at Nvidia with Graviton4 and Trainium3

Amazon's AWS is sharpening its AI edge with custom chipsan upgraded Graviton4 CPU and a forthcoming Trainium3 GPUthat could start chipping away at Nvidia's (NASDAQ:NVDA) market stronghold in AI training and inference. CNBC reports AWS will soon launch a Graviton4 update boasting 600 Gbps of network bandwidth, courtesy of its Annapurna Labs design, with availability expected by month's end. Later this year, AWS plans to roll out Trainium3, promising 50% better energy efficiency versus Trainium2, which underpins Anthropic's Claude Opus 4 model. While Nvidia's Blackwell GPU retains a rawperformance lead, Trainium2 already offers superior cost-performance ratios, according to AWS Senior Director Gadi Hutt. Developers eyeing Trainium will need to retool workloads away from Nvidia's CUDA ecosystem and validate modelaccuracy parity on AWS's frameworks. Nvidia has dominated AI compute thanks to unmatched throughput and the ubiquity of CUDA in developer toolchains. By delivering strong price-performance and energy gains via Graviton4 and Trainium3, AWS aims to lure hyperscalers and cost-sensitive enterprises that run massive inference fleets or large-scale training jobs. If AWS can minimize migration friction and prove equivalent accuracy, it could open the door for a meaningful shift in AI infrastructure spend. The real test will come when Graviton4 benchmarks are published and Trainium3 previews hit developer hands. Watch for cloudnative AI workloads running on non-CUDA stacks and for enterprise case studies highlighting total cost-of-ownership savings. Those signals will reveal whether AWS can genuinely erode Nvidia's GPU hegemony. This article first appeared on GuruFocus. Error in retrieving data Sign in to access your portfolio Error in retrieving data

AWS' custom chip strategy is showing results, and cutting into Nvidia's AI dominance
AWS' custom chip strategy is showing results, and cutting into Nvidia's AI dominance

CNBC

time4 days ago

  • Business
  • CNBC

AWS' custom chip strategy is showing results, and cutting into Nvidia's AI dominance

Amazon Web Services is set to announce an update to its Graviton4 chip that includes 600 gigabytes per second of network bandwidth, what the company calls the highest offering in the public cloud. Ali Saidi, a distinguished engineer at AWS, likened the speed to a machine reading 100 music CDs a second. Graviton4, a central processing unit, or CPU, is one of many chip products that come from Amazon's Annapurna Labs in Austin, Texas. The chip is a win for the company's custom strategy and putting it up against traditional semiconductor players like Intel and AMD. But the real battle is with Nvidia in the artificial intelligence infrastructure space. At AWS's re:Invent 2024 conference last December, the company announced Project Rainier – an AI supercomputer built for startup Anthropic. AWS has put $8 billion into backing Anthropic. AWS Senior Director for Customer and Project Engineering Gadi Hutt said Amazon is looking to reduce AI training costs and provide an alternative to Nvidia's expensive graphics processing units, or GPUs. Anthropic's Claude Opus 4 AI model is trained on Trainium2 GPUs, according to AWS, and Project Rainier is powered by over half a million of the chips – an order that would have traditionally gone to Nvidia. Hutt said that while Nvidia's Blackwell is a higher-performing chip than Trainium2, the AWS chip offers better cost performance. "Trainium3 is coming up this year, and it's doubling the performance of Trainium2, and it's going to save energy by an additional 50%," he said. The demand for these chips is already outpacing supply, according to Rami Sinno, director of engineering at AWS' Annapurna Labs. "Our supply is very, very large, but every single service that we build has a customer attached to it," he said. With Graviton4's upgrade on the horizon and Project Rainier's Trainium chips, Amazon is demonstrating its broader ambition to control the entire AI infrastructure stack, from networking to training to inference. And as more major AI models like Claude 4 prove they can train successfully on non-Nvidia hardware, the question isn't whether AWS can compete with the chip giant — it's how much market share it can take. The release schedule for the Graviton4 update will be provided by the end of June, according to an AWS spokesperson.

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