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Can any company, big or small, really topple Nvidia\u2019s AI chip dominance? Maybe not. But there are hundreds of billions of dollars of revenue for those that can even peel off a chunk of it for themselves, Amazon CEO Andy Jassy said this week.<\/p>\n
As expected, the company announced during the AWS Re:Invent conference the next generation of its Nvidia-competitor AI chip, Trainium3, which is four times faster yet uses less power than the current Trainium2. Jassy revealed a few tidbits about the current Trainium in a post on X<\/a> that shows why the company is so bullish on the chip.<\/p>\n He said the Trainium2 business \u201chas substantial traction, is a multi-billion-dollar revenue run-rate business, has 1M+ chips in production, and 100K+ companies using it as the majority of Bedrock usage today.\u201d<\/p>\n Bedrock is Amazon\u2019s AI app development tool that allows companies to pick and choose among many AI models.<\/p>\n Jassey said Amazon\u2019s AI chip is winning among the company\u2019s enormous roster of cloud customers because it \u201chas price-performance advantages over other GPU options that are compelling.\u201d In other words, he believes it works better and costs less than those \u201cother GPUs\u201d out there in the market. <\/p>\n That is, of course, Amazon\u2019s classic MO<\/a>, offering its own homegrown tech at lower prices.<\/p>\n Additionally, AWS CEO Matt Garman offered even more insight, in an interview with CRN<\/a>, about one customer responsible for a big chunk of those billions in revenue: No shock here, it\u2019s Anthropic.<\/p>\n Techcrunch event<\/p>\n \n\t\t\t\t\t\t\t\t\tSan Francisco<\/span> \u201cWe\u2019ve seen some enormous traction from Trainium2, particularly from our partners at Anthropic who we\u2019ve announced Project Rainier, where there\u2019s over 500,000 Trainium2 chips helping them build the next generations of models for Claude,\u201d Garman said.<\/p>\n Project Rainier is Amazon\u2019s most ambitious AI cluster of servers, spread across multiple of data centers in the U.S. and built to serve Anthropic\u2019s skyrocketing needs. It came online in October. <\/a> Amazon is, of course, a major investor in Anthropic<\/a>. In exchange, Anthropic made AWS its primary model training partner, even though Anthropic is now also offered on Microsoft\u2019s cloud, via Nvidia\u2019s chips. <\/a><\/p>\n OpenAI is now also using AWS in addition Microsoft\u2019s cloud. But the OpenAI partnership couldn\u2019t have contributed much to Trainium\u2019s revenue because AWS is running it on Nvidia chips and systems, the cloud giant said.<\/a><\/p>\n Indeed, only a few U.S. companies like Google, Microsoft, Amazon, Meta have all the engineering pieces \u2014 silicon chip design expertise, homegrown high-speed interconnect and networking technology \u2014 to even attempt true competition with Nvidia. (Remember, Nvidia cornered the market on one major high-performance networking tech in 2019 when CEO Jensen Huang outbid Intel and Microsoft to buy Infiniband hardware maker, Mellanox<\/a>.)<\/p>\n On top of that, AI models and software built to be served up by Nvidia\u2019s chips also rely on Nvidia\u2019s proprietary Compute Unified Device Architecture (CUDA) software. CUDA allows the apps to use the GPUs for parallel processing compute among other tasks. Just like the Intel vs. SPARC chip war of yesterday, it\u2019s no small thing to re-write an AI app for a non-CUDA chip.<\/a><\/p>\n Still, Amazon may have a plan for that. As we previously reported, the next generation of its AI chip, Trainium4, will be built to interoperate with Nvidia\u2019s GPUs in the same system. Whether that helps peel more business away from Nvidia or simply reinforces its dominance, but on AWS\u2019s cloud, remains to be seen. <\/p>\n It may not matter to Amazon. If it is already on track to do multi-billion-dollars from Trainium2 chip, and the next generation will be that much better, it may be winner enough.<\/p>\n<\/div>\n
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\n\t\t\t\t\t\t\t\t\t\t\t\t\tOctober 13-15, 2026<\/span>\n\t\t\t\t\t\t\t<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n