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Models

Foundation, generative, multimodal and specialised models.

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2023

  • Mar 2023 Runway Gen-2

    Runway Gen-2 is a multimodal video generation system announced in March 2023 that turns text, images or video clips into new video, and was among the first commercially available text-to-video models.

    MultimodalGenerative modelsCreative tools

  • Feb 24, 2023 LLaMA

    A family of foundation language models from Meta AI, released in 7B to 65B parameter sizes and trained on public data; its 13B model was reported to beat GPT-3 on most benchmarks.

    Large language modelsOpen sourceFoundation models

  • Feb 6, 2023 Runway Gen-1

    Runway Gen-1 is a video-to-video diffusion model released in February 2023 that restyles existing footage from text or image prompts while keeping the source video's structure. It was among the first commercially available video-generation models.

    MultimodalGenerative modelsCreative tools

  • 2023 ChatGLM-6B

    An open bilingual chat model from Zhipu AI and Tsinghua KEG with about 6.2 billion parameters, small enough to run on one consumer GPU, with weights fully open for research.

    Large language modelsOpen sourceChina

  • 2023 Cohere Command

    Cohere's first flagship instruction-following generative model, released in 2023 and distributed through Cohere's API and cloud marketplaces such as Amazon SageMaker JumpStart and Oracle Cloud Infrastructure, later superseded by Command R and deprecated in 2025.

    Large language modelsEnterpriseFoundation models

2022

2021

  • Dec 23, 2021 ERNIE 3.0 Titan

    ERNIE 3.0 Titan is a Chinese pre-trained language model with over 260 billion parameters, described by its authors as the largest dense Chinese model of its time and reported to beat state-of-the-art systems on 68 NLP datasets.

    Large language modelsResearch historyChina

  • 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

  • Aug 2021 Jurassic-1

    Jurassic-1 is the first family of large language models from AI21 Labs, announced with the AI21 Studio developer platform in August 2021. Its largest model, Jumbo, has 178 billion parameters.

    Large language modelsFoundation modelsDeveloper tools

  • Jul 7, 2021 OpenAI Codex (2021 model)

    OpenAI Codex is a 2021 GPT language model fine-tuned on public code from GitHub. It translates natural language into code, and was introduced alongside the HumanEval benchmark for testing code correctness.

    Large language modelsResearch historyDeveloper tools

  • 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

  • Jun 2021 GPT-J-6B

    GPT-J-6B is a six-billion-parameter open language model released by EleutherAI in June 2021 under the Apache 2.0 license. Its published scores sit close to GPT-3 Curie, making it a widely used free baseline for large-model research.

    Large language modelsResearch historyOpen source

  • 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

  • Mar 21, 2021 GPT-Neo

    GPT-Neo is a family of open text-generation models released by EleutherAI in March 2021 at 125M, 1.3B and 2.7B parameters, built to replicate the GPT-3 architecture and distributed with freely downloadable weights under an MIT license.

    Large language modelsResearch historyOpen source

  • 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

2011

  • Feb 2011 IBM Watson

    IBM Watson is a question-answering computer system built by an IBM research team led by David Ferrucci; in February 2011 it defeated the two foremost all-time champions of the televised quiz show Jeopardy!

    Research historyEnterpriseReasoning