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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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2023
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Dec 6, 2023
AMD Instinct MI300X
AMD's data-center GPU for generative AI, released in December 2023. Built on the CDNA 3 architecture with a chiplet design, it leads with 192 GB of HBM3 memory, which AMD contrasted with the 80 GB on Nvidia's H100.
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Mar 2023
NVIDIA H800
The H800 is a China-market version of NVIDIA's H100 data-center GPU, adapted to fit the US export rules of October 2022 by cutting chip-to-chip transfer speed. It was later used to train DeepSeek-V3 and was covered by tighter US controls in October 2023.
2020
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May 14, 2020
NVIDIA A100
NVIDIA's A100 is a data-center GPU, the first built on the Ampere architecture. Announced on 14 May 2020, it introduced third-generation Tensor Cores, the TF32 format and Multi-Instance GPU, and became a standard building block for training large language models.
2010
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Nov 9, 2010
NVIDIA GeForce GTX 580
A consumer graphics card NVIDIA released in November 2010 on its Fermi architecture. Two of them, each with 3 GB of memory, later trained AlexNet, the network that won ILSVRC-2012 and which NVIDIA's timeline credits with sparking the era of modern AI.
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Tenstorrent Blackhole
Blackhole is Tenstorrent's AI accelerator chip; Galaxy Blackhole is a server holding 32 of them, rated at 23 PFLOPS of block FP8, with Ethernet links wiring chips and clusters together.