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

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

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2025 that reads text, tables, equations and embedded media across thousands of scripts and languages, and was later superseded by newer OCR versions.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

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

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

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

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

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

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

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

Grok-1 is xAI's first large language model, announced on 3 November 2023 as the engine of the Grok chatbot. Its 314-billion-parameter weights were released openly in March 2024.

Large language modelsOpen sourceFoundation models

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

RT-2 is a vision-language-action model from Google DeepMind, announced on 28 July 2023, that turns images and text instructions into robot actions written as text tokens. In over 6,000 trials it reached 62% on unseen scenarios, up from 32% for RT-1.

MultimodalRoboticsComputer vision

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

PaLM 2 is Google's second-generation Pathways language model, announced on 10 May 2023 in four sizes and used across more than 25 Google products, including Bard.

Large language modelsEnterpriseConsumer apps

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

Stable LM is Stability AI's family of open language models, first released in April 2023 as 3B- and 7B-parameter alpha versions under licenses that allow commercial use of the base models and research-only use of the instruction-tuned ones.

Large language modelsOpen sourceFoundation models

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

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

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

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

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

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

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

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

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

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

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