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The chips that train and run AI models: GPUs, TPUs and other accelerators, and which models were trained on them.
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2025
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Dec 2, 2025
AWS Trainium3
AWS Trainium3 is AWS's first 3-nanometer AI chip, delivering 2.52 petaflops of FP8 compute per chip and scaling to 144 chips in a Trn3 UltraServer, available through Amazon EC2 from December 2025.[^1][^2]
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Mar 18, 2025
NVIDIA GB300 NVL72
A rack-scale NVIDIA system announced in March 2025 that links 72 Blackwell Ultra GPUs and 36 Grace CPUs into one unit, rated at 1.5 times the AI performance of GB200 NVL72.
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2025
Google TPU7x (Ironwood)
TPU7x (Ironwood) is Google's seventh-generation TPU: 192 GB of high-bandwidth memory per chip, FP8 matrix units, 9,216 chips per pod, and a programming model that exposes two devices per chip.
2022
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Mar 22, 2022
NVIDIA H100
The NVIDIA H100 is the first data-center GPU built on NVIDIA's Hopper architecture, announced in March 2022 with 80 billion transistors, HBM3 memory, FP8 Tensor Cores and a Transformer Engine aimed at large language models.
2016
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Apr 5, 2016
NVIDIA Tesla P100
The Tesla P100, announced by NVIDIA in April 2016, was the first data-center GPU on the Pascal architecture, and the first to combine stacked HBM2 memory, half-precision math aimed at deep learning and the NVLink interconnect.