Enterprises put non-Nvidia chips 14 points ahead of Nvidia's next-gen GPUs on their evaluation lists
When enterprise buyers build out their next AI accelerator evaluation list this cycle, they're more likely to put a non-Nvidia chip on it than Nvidia's own next-generation GPU. According to VentureBeat's July VB Pulse survey of 170 AI infrastructure respondents , 39.4% said they're likely to evaluate non-Nvidia accelerators — AWS Trainium, Google TPU, AMD Instinct, Intel Gaudi or in-house ASICs —…
Enterprise buyers are increasingly considering non-Nvidia chips for their AI accelerator evaluation lists, with 39.4% of respondents likely to evaluate alternatives such as AWS Trainium, Google TPU, AMD Instinct, Intel Gaudi, or in-house ASICs in the next 12 months, compared to 25.3% opting for Nvidia's next-generation GPUs. This 14-point gap highlights a shift in strategy, as organizations seek greater flexibility and options in their AI infrastructure rather than relying solely on Nvidia.
Despite this trend, Nvidia remains the dominant choice in production environments, with enterprises focusing on optimizing and expanding their existing infrastructure before making significant platform changes. The data also shows increased operational efficiency among enterprises, with Microsoft Azure seeing the largest growth in production adoption, followed by Google's Gemini and OpenAI.
These findings suggest that while enterprises are deploying more AI infrastructure, they are also becoming more capable operators with improved architectures and higher standards for uptime, reliability, and throughput.
Brief written by urgent.news from VentureBeat's own syndicated text. Machine-written — may contain errors; check the original before relying on it.
