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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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2024
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Mar 18, 2024
NVIDIA B200 (Blackwell)
NVIDIA's data-center GPU for the Blackwell generation, announced in March 2024 as the successor to Hopper, built from two joined dies and paired with NVLink and FP4 support for large-scale AI training and inference.
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.
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.
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.
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2020
Google TPU v4
Google's TPU v4 is a machine-learning chip and supercomputer deployed since 2020, built into 4,096-chip pods with optically reconfigurable networking; PaLM and Gemini models were trained on it.
2017
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Sep 12, 2017
Apple A11 Bionic
Apple's 2017 smartphone chip, announced with the iPhone X: a six-core CPU, an Apple-designed three-core GPU and a dual-core neural engine built for on-device machine learning such as Face ID.
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May 10, 2017
NVIDIA Tesla V100
NVIDIA's first data-center GPU built on its Volta architecture, announced in May 2017. It added Tensor Cores, dedicated matrix-multiply units; OpenAI later trained its GPT-3 models on V100s.
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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.
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NVIDIA DGX Spark
NVIDIA's DGX Spark is a desktop-sized AI computer built on the GB10 Grace Blackwell Superchip, pairing a 20-core Arm CPU with a Blackwell GPU and up to 128 GB of unified memory for running large models locally.