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Models

Foundation, generative, multimodal and specialised models.

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2026

2025

  • Sep 2025 Qwen3-Next

    Qwen3-Next is an open-weight model from Alibaba's Qwen team, released in September 2025 under Apache 2.0. It has 80B total parameters, only 3B active per token, and a hybrid attention design later used in Qwen3.5.

    Large language modelsOpen sourceChina

  • Jul 2025 Skild Brain

    Skild Brain is Skild AI's general-purpose foundation model for robots, trained in a universe of 100,000 different machines and meant to be fitted to existing hardware rather than built for one task.

    EnterpriseDeep learningFoundation models

  • May 21, 2025 Aurora

    Aurora is a foundation model for the Earth system, trained on more than a million hours of geophysical data. It outperforms operational forecasts for weather, air quality, ocean waves and tropical cyclone tracks at far lower computational cost.

    Deep learningFoundation modelsScience

  • May 1, 2025 Falcon-H1

    Falcon-H1 is a family of open-weight language models that runs Transformer attention and state space layers in parallel, released in sizes from 0.5B to 34B parameters under the Falcon-LLM Licence.

    Large language modelsOpen sourceFoundation models

  • Apr 22, 2025 π0.5 (pi-zero-point-five)

    π0.5 is a vision-language-action model from Physical Intelligence, released in April 2025, built to generalize to unfamiliar homes and trained by co-training on many kinds of robot and web data.

    Deep learningFoundation modelsMultimodal

  • Feb 20, 2025 Figure Helix

    Helix is Figure's vision-language-action model for humanoid control, pairing a 7-billion-parameter vision-language model with a fast 80-million-parameter action policy, trained on about 500 hours of teleoperated data and run entirely on onboard GPUs.

    Deep learningFoundation modelsMultimodal

2024

  • Oct 31, 2024 π0 (pi-zero)

    π0 is a generalist robot policy from Physical Intelligence, built by adapting a 3-billion-parameter vision-language model with flow matching so one model can output fast, continuous motor commands for dexterous manipulation.

    Deep learningFoundation modelsMultimodal

  • Oct 22, 2024 Stable Diffusion 3.5

    A family of text-to-image models from Stability AI, announced in October 2024: the 8.1-billion-parameter Large, a 4-step Turbo variant and the 2.5-billion-parameter Medium, released under a community licence.

    Open sourceGenerative modelsCreative tools

  • Jul 23, 2024 Llama 3.1 (including 405B)

    Llama 3.1, released on 23 July 2024, added a 405-billion-parameter model to the Llama 3 family and extended its context to 128,000 tokens. Meta called the 405B the largest and most capable openly available foundation model.

    Large language modelsOpen sourceFoundation models

  • Jun 13, 2024 OpenVLA

    OpenVLA is a 7-billion-parameter open-source vision-language-action model trained on 970,000 real robot demonstrations, released with checkpoints and code so that other groups can fine-tune and run it on their own robots.

    Open sourceFoundation modelsMultimodal

  • May 8, 2024 AlphaFold 3

    AlphaFold 3 is a structure-prediction model from Google DeepMind and Isomorphic Labs, announced on 8 May 2024. It predicts the structures and interactions of proteins, DNA, RNA, ligands and chemical modifications, extending structure prediction beyond proteins alone.[^1]

    Deep learningGenerative modelsScience

  • May 2024 Octo

    Octo is an open-source generalist robot policy: a transformer-based diffusion model trained on 800,000 robot trajectories that can drive a range of robots out of the box and be fine-tuned to new setups.

    Open sourceDeep learningFoundation models

  • Apr 18, 2024 Llama 3

    Llama 3 is an open model family from Meta, released on 18 April 2024 at 8 billion and 70 billion parameters. It was pretrained on over 15 trillion tokens of publicly available data.

    Large language modelsOpen sourceFoundation models

  • Feb 22, 2024 Stable Diffusion 3

    Stable Diffusion 3, announced by Stability AI on 22 February 2024, is a suite of 800 million to 8 billion parameter models that pairs a diffusion transformer with flow matching.

    Open sourceGenerative modelsCreative tools

  • Feb 21, 2024 Gemma

    Gemma is a family of lightweight open language models from Google DeepMind, released in February 2024 in 2B and 7B sizes, built from the same research and technology as Gemini and offered for commercial use under Google's terms.

    Large language modelsOpen sourceDeveloper tools

  • Jan 9, 2024 DeepSeekMoE

    DeepSeekMoE is a mixture-of-experts architecture from DeepSeek, released in January 2024, that splits experts finely and keeps a few shared experts always active so that each expert holds focused knowledge. Its 16B open-weights model matched larger dense models at a fraction of the computation.

    Large language modelsOpen sourceChina

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 15, 2021 RoseTTAFold

    RoseTTAFold is a three-track neural network for protein structure prediction, published by the Baker lab in 2021; its accuracy approached AlphaFold2's at CASP14, it models protein–protein complexes from sequence alone, and it is distributed as open code with a public web server.

    Research historyOpen sourceDeep learning

  • 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

  • Nov 30, 2020 AlphaFold2

    AlphaFold2 is DeepMind's protein structure prediction system, announced in 2020. It reached accuracy competitive with experimental methods in many cases, and work in this area received half of the 2024 Nobel Prize in Chemistry.

    Research historyDeep learningScience

  • 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

2017

  • Dec 5, 2017 AlphaZero

    AlphaZero is a general game-playing system from DeepMind, described in a preprint in December 2017, that reached a superhuman level in chess, shogi and Go within 24 hours starting from random play, using only the rules of each game.

    Research historyDeep learningReasoning

  • Oct 18, 2017 AlphaGo Zero

    A DeepMind Go program that learned the game from scratch by playing against itself, using no human game records, and beat earlier versions of AlphaGo within days.

    Research historyDeep learningReasoning