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Models

Foundation, generative, multimodal and specialised models.

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2025

2024

2023

2022

2021

  • Dec 8, 2021 Gopher

    Gopher is DeepMind's 280-billion-parameter language model, announced in December 2021 alongside a study of what scale does to language models and a companion taxonomy of their risks.

    Large language modelsResearch historyEurope

  • Oct 11, 2021 Megatron-Turing NLG 530B

    Megatron-Turing NLG 530B is a 530-billion-parameter language model announced by NVIDIA and Microsoft on 11 October 2021, then the largest monolithic transformer language model, trained on NVIDIA's Selene supercomputer with Megatron-LM and DeepSpeed combined.

    Large language modelsFoundation modelsHardware & compute

  • Jul 5, 2021 ERNIE 3.0

    ERNIE 3.0 is a 10-billion-parameter pre-trained language model from 2021 that trains on plain text plus a large-scale knowledge graph and fuses auto-encoding and auto-regressive networks, so one model handles both language understanding and generation.

    Large language modelsResearch historyChina

  • May 18, 2021 LaMDA

    LaMDA is a family of conversational language models that Google announced in 2021 and described in a 2022 paper, notable for its work on safety and factual grounding in dialogue and for later powering Bard.

    Large language modelsResearch historyConsumer apps

  • Jan 5, 2021 CLIP

    An image-text model from OpenAI that learns to match pictures with their captions. Trained on about 400 million image-caption pairs, it can classify images by comparing them against written prompts, with no task-specific training.

    Open sourceFoundation modelsMultimodal

  • Jan 5, 2021 DALL·E

    DALL·E is OpenAI's text-to-image model unveiled on 5 January 2021: a 12-billion-parameter transformer trained on 250 million text-image pairs that generates a picture token by token from a caption.

    MultimodalGenerative modelsCreative tools

2020

  • May 28, 2020 GPT-3

    GPT-3 is an autoregressive language model with 175 billion parameters, described in a May 2020 paper. It could perform new tasks from a few examples in the prompt, without any gradient updates, and it was first offered through OpenAI's API.

    Large language modelsResearch historyFoundation models

  • Jan 28, 2020 Meena

    Meena is a 2.6-billion-parameter open-domain chatbot from Google, trained end-to-end on filtered social media conversations. Its 2020 paper introduced the SSA human-evaluation metric and linked next-token perplexity to human-judged chat quality. The work was later renamed LaMDA.

    Large language modelsResearch historyConsumer apps

2019

2018

  • Oct 11, 2018 BERT

    BERT is a language model from Google that reads text in both directions and is pre-trained by filling in masked words. Fine-tuned per task, it set new records on question answering and language-understanding benchmarks and later went into Google Search.

    Large language modelsResearch historyOpen source

  • Jun 11, 2018 GPT-1

    GPT-1 was OpenAI's first generative pre-trained transformer, published in June 2018. It showed that one language model, pre-trained on unlabelled text and then fine-tuned, could improve results on many language tasks.

    Large language modelsResearch historyOpen source