Models

NVIDIA Nemotron 3 is an open family of hybrid mixture-of-experts language models, announced in December 2025 in Nano, Super and Ultra sizes, with up to one million tokens of context.

Large language modelsOpen sourceAgents & tool use

Olmo 3 is the third generation of the Allen Institute for AI's fully open language models, announced on 20 November 2025 in 7B and 32B dense Transformer sizes, with a 65,536-token context and all datasets openly available.

Large language modelsOpen sourceReasoning

SAM 3 is Meta's segmentation model from November 2025. It finds, segments and tracks every instance of a concept named by a short text prompt or an example image, and Meta reported it doubles the accuracy of existing systems on this task.

Open sourceFoundation modelsData & datasets

DeepSeek-OCR is an open-source model of about 3B parameters that renders long text as 2D images and reads it back from a small number of vision tokens, testing whether optical compression can stand in for very long text contexts.

Open sourceChinaMultimodal

Nemotron Nano 2 is NVIDIA's 9B reasoning model, built on a hybrid Mamba-Transformer design and released with open weights and most of its training data; NVIDIA reports much higher throughput than similar-sized models.

Large language modelsOpen sourceReasoning

SmolLM3 is a 3-billion-parameter open model released by Hugging Face on 8 July 2025. It supports six languages and up to 128K tokens of context, with switchable reasoning, under Apache 2.0.

Large language modelsOpen sourceReasoning

The largest model in Ai2's OLMo 2 family: a 32-billion-parameter language model released with its data, code, weights and training details, and reported to outperform GPT-3.5-Turbo and GPT-4o mini on academic benchmarks.

Large language modelsOpen sourceData & datasets

Mistral OCR is a document-understanding API released by Mistral AI on 6 March 2025 that reads text, tables, equations and embedded media across thousands of scripts and languages, and was later superseded by newer OCR versions.

EnterpriseData & datasetsComputer vision

Phi-4 is Microsoft's 14-billion-parameter dense decoder-only language model, built with a data-quality-first recipe heavy on synthetic data and released with full weights under the MIT licence in January 2025.

Large language modelsOpen sourceReasoning

OLMo 2 is the second generation of the Allen Institute for AI's fully open language model family, released in 7B and 13B sizes with weights, data, code and training recipes all public.

Large language modelsOpen sourceData & datasets

SmolLM2 is Hugging Face's second family of small language models, released in November 2024 at 135M, 360M and 1.7B parameters, with open weights and a data-centric training recipe.

Large language modelsOpen sourceConsumer apps

Molmo is a family of open vision-language models released by Ai2 on 25 September 2024 that can point at objects in images, with weights, code, data and evaluations published openly.

Open sourceMultimodalData & datasets

SAM 2 is Meta's 2024 successor to the Segment Anything Model. It segments objects in both images and videos in real time, and its release included the SA-V video dataset.

Open sourceFoundation modelsData & datasets

SmolLM is a family of small language models with 135M, 360M and 1.7B parameters, released openly by Hugging Face in July 2024 for on-device use and trained on a purpose-built corpus of generated textbooks, code and filtered web text.

Large language modelsOpen sourceConsumer apps

Nemotron-4 340B is a family of open models from NVIDIA, released on 14 June 2024 as base, instruct and reward models. It was built to generate synthetic data for training other language models, and it fits on a single eight-GPU DGX H100.

Large language modelsOpen sourceEnterprise

OpenELM is a family of small open language models from Apple, published in four sizes from 270M to 3B parameters with its training framework, logs, checkpoints and MLX conversion code.

Large language modelsResearch historyOpen source

EvoLLM-JP is a Japanese model from Sakana AI built by evolutionarily searching merges of three open-source models instead of training from scratch; the 7B result has mathematics ability none of its sources had alone.

Large language modelsResearch historyOpen source

StarCoder2 is a family of open code models in 3B, 7B and 15B sizes, released in February 2024 by BigCode (Hugging Face and ServiceNow) with NVIDIA and trained on The Stack v2, published together with its dataset and training code.

Large language modelsOpen sourceData & datasets

A Google DeepMind generative world model with 11 billion parameters that turns text, images or sketches into controllable virtual worlds, described as the first generative interactive environment trained on unlabelled internet videos without action labels.

Research historyGenerative modelsSimulation

Aya 101 is a 13-billion-parameter, instruction-tuned language model from Cohere For AI that follows instructions in 101 languages. It was released under Apache 2.0 in February 2024.

Large language modelsOpen sourceFoundation models

Phi-2 is a 2.7-billion-parameter base language model from Microsoft Research, announced on 12 December 2023. Microsoft reported that it matched or beat models up to 25 times larger on complex benchmarks, making it a reference point for small-model training.

Large language modelsOpen sourceReasoning

GNoME is a Google DeepMind deep-learning tool, announced on 29 November 2023, that predicts new inorganic crystals; it produced 2.2 million candidate structures, of which 380,000 were predicted to be stable.

Deep learningData & datasetsScience

Phi-1.5 is a 1.3-billion-parameter language model from Microsoft Research, trained on curated synthetic "textbook" text rather than web crawls; its report claims natural-language performance comparable to models five times larger.

Large language modelsOpen sourceReasoning

Phi-1 is a 1.3-billion-parameter Transformer language model for Python from Microsoft Research, which showed that filtered and synthetic "textbook quality" training data can partly substitute for model and data scale.

Large language modelsOpen sourceData & datasets

StarCoder is an open-access code language model of about 15.5 billion parameters, released on 4 May 2023 by the BigCode project led by Hugging Face and ServiceNow.

Large language modelsOpen sourceData & datasets

Pythia is a suite of 16 open language models from EleutherAI, ranging from 70 million to 12 billion parameters, all trained on the same data in the same order, with 154 public checkpoints from each training run.

Large language modelsResearch historyOpen source

RT-1 is a transformer-based model for real-world robot control, trained on over 130,000 episodes collected with 13 robots and reported to perform more than 700 language instructions at a 97% success rate.

Research historyFoundation modelsMultimodal

Galactica is a large language model for science, unveiled by Meta AI and Papers with Code in November 2022. Its public demo was taken down about three days later, after users found it produced fake papers.

Large language modelsResearch historyOpen source

GLM-130B is a 130-billion-parameter open bilingual Chinese–English dense language model from Tsinghua University's KEG group and Zhipu AI, built to give researchers an open model that matches GPT-3 at the hundred-billion scale.

Large language modelsResearch historyOpen source

Imagen is a text-to-image diffusion model announced by Google Research in May 2022, known for pairing a frozen large language model with diffusion and for the DrawBench benchmark; Google did not release it publicly.

Research historyGenerative modelsCreative tools

Gato is a generalist agent from DeepMind, announced on 12 May 2022. A single network with one set of weights handles text, images, Atari games and robot control, aiming at multi-task, multi-embodiment learning.

Research historyAgents & tool useMultimodal

OPT-175B is a 175-billion-parameter language model from Meta AI, announced in May 2022. Meta said it was the first model of its size released with both pretrained weights and the code to train and use them.

Large language modelsResearch historyOpen source

Flamingo is a DeepMind visual language model announced in April 2022. It takes prompts that mix images, videos and text and replies in language, learning new tasks from only a few examples.

Large language modelsResearch historyMultimodal

GPT-NeoX-20B is a 20-billion-parameter open autoregressive language model released by EleutherAI in February 2022, with weights under Apache 2.0 and its training code, described by its makers as the largest publicly accessible general-purpose model of its kind at the time.

Large language modelsResearch historyOpen source

AlphaCode is a DeepMind code-generation system for competitive programming, announced in February 2022. On Codeforces contests held after its training data, it reached an estimated rank around the median participant. A Gemini-based AlphaCode 2 followed in December 2023.

Large language modelsResearch historyCode

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

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

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

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

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

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

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

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

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

MuZero is a DeepMind reinforcement-learning algorithm that pairs tree-based search with a learned model. It reached superhuman play in Atari, Go, chess and shogi without being given the environment's rules.

Research historyDeep learningReasoning

T5 is a family of Google Transformer models that recasts every language task as text in, text out. Its 11-billion-parameter version set state of the art on several benchmarks, and the code, models and C4 dataset were released openly.

Large language modelsOpen sourceFoundation models

ERNIE 2.0 is Baidu's pre-trained language model framework, published in 2019, which builds pre-training tasks incrementally through continual multi-task learning and reported results above BERT and XLNet on English and Chinese benchmarks.

Large language modelsResearch historyOpen source

Baidu's first ERNIE pre-trained language model, released in March 2019, added entity- and phrase-level masking to BERT-style pre-training and reported state-of-the-art results on five Chinese NLP tasks.

Large language modelsResearch historyOpen source

AlphaStar is a DeepMind system that plays StarCraft II. In 2019 it reached Grandmaster level with all three races, ranking above 99.8% of active players on Battle.net.

Research historyDeep learningReasoning

DeepMind's first protein-structure prediction system, which placed first overall in the 2018 CASP13 blind assessment by estimating probability distributions of distances between residues.

Research historyDeep learningScience