Amazon Web Services (AWS) has officially launched its third-generation custom AI chip, Trainium3, challenging Nvidia's dominance in the GPU market. The cloud giant claims the new chip quadruples performance over its predecessor and reduces AI model training and inference costs by up to 50% compared to equivalent GPU systems.
AI video startup Decart's tests revealed that Trainium3 delivers four times higher frame rates in video generation compared to other chips, including Nvidia's offerings. Despite the rise of custom chips, Nvidia's market position remains formidable in the near term. Ron Diamant, AWS VP and Trainium Chief Architect, emphasized: "Ultimately, the key advantage lies in cost efficiency."
The AI industry is increasingly diversifying its chip suppliers. Meta Platforms is reportedly in talks with Google to purchase billions worth of TPU chips, while OpenAI has partnered with AMD and Broadcom. Trainium3 has already been adopted by clients including Anthropic and Decart.
Decart co-founder and CEO Dean Leitersdorf shared that after testing various competing chips, Trainium3 enabled a technical breakthrough, allowing their AI-powered video generation app Lucy to achieve real-time rendering without glitches. "Before this, we could only run for 1.5 to 2 seconds before noise appeared," Leitersdorf recalled. "Trainium lets us run a larger, smarter model that doesn't crash quickly."
AWS's custom chip division, Annapurna Labs, has been designing data center chips since its 2015 acquisition. While Trainium3's adoption is growing—with clients like Karakuri, Metagenomi, and Ricoh—many AWS customers remain Nvidia buyers. For instance, Anthropic uses over 1 million Trainium2 chips for its Claude AI model, yet Nvidia recently invested $10 billion in the company as part of a major chip supply deal.
Nvidia responded to the competitive landscape by stating its platform remains "a generation ahead of the industry" and uniquely capable of running all AI models. The company maintains that its chips offer superior performance, versatility, and replaceability compared to custom solutions from AWS and Google.
The market is evolving toward multi-supplier competition rather than complete displacement of Nvidia's solutions, as AI companies seek to mitigate risks and optimize costs. While custom chips gain traction, Nvidia's entrenched position appears secure for now.
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