What Are Robot Action Models?
12 entriesRobot action models are AI models that turn perception and instructions into robot actions, including vision-language-action (VLA) models, world action models and integrated systems for humanoids and arms. They are appearing very quickly, and a 31 October 2026 LinkedIn post by Jens Peder Kristensen of KeyResearch (embodied.guide) reviews 30 leading models and picks a Top 15 for 2026. The author says he prioritized how readily a model handles new tasks, through zero-shot generalization, learning from demonstrations, adaptation and transfer between robots, and also weighed physical performance and the strength of evidence. He states that it is an editorial assessment, not a standardized head-to-head benchmark, that independently tested results count more than company claims, and that the order is likely to change. This page reproduces his list of names, links each entry to a primary source where one could be found, and says plainly where one could not. Descriptions are paraphrased, are not rankings by this site, and the model claims were not independently verified here.
The Top 15 Robot Action Models for 2026 (Editorial List)
15 entriesThe order is the post author's. Each description paraphrases his one-line note; the link goes to a company or project page, not to evidence for the ranking.
Primary Sources and Open Tooling
7 entriesPapers, repositories and coverage that help verify or reproduce claims.
Frequently Asked Questions
What is a robot action model?
An AI model that maps what a robot perceives, plus an instruction, to actions. Common families are vision-language-action (VLA) models, which start from a vision-language model, and world action models, which start from video or world models. See the Physical AI and World Action Models pages.
How was the Top 15 chosen?
By the post's author, who says he reviewed 30 models and prioritized handling of new tasks: zero-shot generalization, learning from demonstrations, adaptation and transfer between robots, with physical performance and the strength of evidence also considered. He describes it as an editorial assessment drawing on papers, public benchmarks and company demonstrations, not a standardized benchmark.
Is this a benchmark or a ranking by this site?
No. The order and the entries come from the LinkedIn post. This page adds links and notes on what could be verified, and it did not test any model.
Which entries could not be verified?
No primary source was found for @Dream-1, and the GO-3, WALL/HOST, VPP2, Dyna-2.1 and UnifoLM-WLA-1.0 names were not confirmed in the company materials found, as the cards note. Skild S1 was also not confirmed on the company site.
Which of these models are open?
Several link to open repositories, including NVIDIA Isaac GR00T, Robbyant LingBot-VLA, Unitree's UnifoLM repository, Galaxea and Perceptron's Isaac 0.5, which Perceptron calls open source. Licences and weights vary, so check each repository. Others, such as the models from Skild, Generalist and Figure, are presented by their companies without public weights.
The post counts nine US and six Chinese models. What does that show?
Only the author's selection. It is not a measure of national research output, and the list is likely to change as new models arrive, as the author notes.
How should I evaluate a robot action model?
Prefer independent tests on your own tasks and robot, check whether results are zero-shot or after fine-tuning, and treat demonstrations and company claims cautiously. See the benchmarks section of the World Action Models and Platforms page.
How current is this page?
Links were checked on 1 November 2026. LinkedIn may ask visitors to sign in. Company sites and announcements were not independently verified beyond the checks noted on each card. Descriptions are paraphrased and are not rankings by this site.