Models

GO-3 Preview is an embodied AI model that AGIBOT announced in October 2026, built on a World Reasoning Action Model; the company says it topped three embodied AI benchmarks and will fully open-source it by the end of 2026.

ChinaFoundation modelsRobotics

FLUX 3 is a multimodal model family from Black Forest Labs, announced on 23 July 2026, covering images, video, audio and action prediction. Its video model became generally available on 4 August 2026.

MultimodalRoboticsGenerative models

Robostral Navigate is Mistral AI's first embodied navigation model: an 8-billion-parameter system that steers wheeled, legged or flying robots from RGB images and a plain-language instruction, using a single ordinary camera and no depth sensor.

RoboticsComputer visionEurope

π0.7 is a general-purpose robot manipulation model from Physical Intelligence that matches fine-tuned specialists on a wide range of dexterous tasks while following new language commands and recombining learned skills in unfamiliar settings.

Foundation modelsMultimodalRobotics

NVIDIA previewed Isaac GR00T N2, a next-generation robot foundation model built on a world action model architecture that the company says more than doubles success on new tasks compared with leading VLA models.

Foundation modelsRoboticsHumanoid robots

An open reasoning vision-language-action model from NVIDIA for humanoid robots, announced in March 2026 as commercially usable and trained on large public robot manipulation datasets.

Open sourceFoundation modelsRobotics

Reka Edge is a 7-billion-parameter vision-language model from Reka AI, released on 11 March 2026, built to take images, video and text and to run locally on laptops, phones and small edge devices.

Open sourceMultimodalRobotics

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

GWM-1 is Runway's first general world model: an autoregressive system that generates 720p video frame by frame in real time and can be steered with camera pose, robot commands or audio.

MultimodalRoboticsGenerative models

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

A robot model from Physical Intelligence trained on demonstrations, human corrections and its own autonomous experience, reported to make espresso, fold laundry and assemble boxes with over 90% success.

Foundation modelsRoboticsReasoning

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

A pair of robotics models announced by Google DeepMind in September 2025: Gemini Robotics 1.5, a vision-language-action model that reasons in natural language before it moves, and Gemini Robotics-ER 1.5, an embodied-reasoning planner that can call tools.

Agents & tool useMultimodalRobotics

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

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

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

Isaac GR00T N1 is an open foundation model for humanoid robots that NVIDIA announced on 18 March 2025. It is designed to be post-trained for a specific robot or task, and it pairs a planning model with quick motion control.

Open sourceFoundation modelsRobotics

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

Gemini Robotics is a vision-language-action model from Google DeepMind, built on Gemini 2.0, that outputs physical actions to control robots. It was announced on 12 March 2025 alongside Gemini Robotics-ER.

MultimodalRoboticsComputer vision

A general-purpose embodied foundation model released by AgiBot on 10 March 2025, built on a Vision-Language-Latent-Action architecture. In the company's tests across five tasks it raised average success rate from 46% to 78%.

ChinaFoundation modelsMultimodal

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

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

NVIDIA Cosmos is a platform of world foundation models that generate physics-based video to train robots and autonomous vehicles, released as open-weight models in January 2025.

Open sourceFoundation modelsRobotics

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

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

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

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

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

NVIDIA's project for a general-purpose foundation model for humanoid robots, announced in March 2024 and followed in March 2025 by Isaac GR00T N1, an open, customizable model released with training data and evaluation scenarios.

Foundation modelsRoboticsHumanoid robots

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

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

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

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

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

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

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

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