Foundation models Compute

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.

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.

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.

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.

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.