# OpenAI Cuts Robotics Team as AI Models Take Over

> OpenAI dissolves standalone robotics team after general-purpose AI models prove capable of direct robot control.
- Title: OpenAI Cuts Robotics Team as AI Models Take Over | Shortify
- Summary: OpenAI dissolves standalone robotics team after general-purpose AI models prove capable of direct robot control.
- Keywords: openai, gpt-6 astra, robotics, ai models, general-purpose models, embodied ai, robot control, nvidia, anthropic, unitree robotics, gemma robotics, deepmind
- Source: BigGo Finance — https://finance.biggo.com/news/2db4f134-c839-4006-bb86-dcb072b67c43
- Author: BigGo Finance
- Published: 2026-11-14T18:15:25+00:00
- Read time: 2 min
- Topics: openai, gpt-6 astra, robotics, ai models, general-purpose models, embodied ai, robot control, nvidia, anthropic, unitree robotics, gemma robotics, deepmind
## OpenAI dissolves robotics team
OpenAI confirmed it dissolved its standalone robotics research team on November 13, merging staff into core research and applications divisions.
## Recruitment shift in two months
Just two months before the dissolution, OpenAI was recruiting robotics talent at salaries up to $500,000.
## Robotics team restructuring
The former robotics researchers moved to the core research division led by Chief Research Officer Mark Chen, while applications staff joined Greg Brockman's division.
## Robotics remains strategic priority
OpenAI stated robotics remains an important part of its long-term technology vision and the restructuring aims to accelerate R&D.
## Previous robotics efforts
OpenAI previously demonstrated the Dactyl robotic hand solving a Rubik's cube in 2019 and ended standalone robotics research in 2020.
## GPT-6 Astra's control capability
OpenAI's technical explanation: general-purpose models like GPT-6 Astra can directly control robots, so robotics research was absorbed into the general foundation-model system.
## Nvidia's test results
Nvidia's GPT-6 Astra direct-control approach achieved a 66.3% task success rate in RoboLab-120 simulation tests.
## Anthropic's test results
Anthropic's Claude Fable 5.2 achieved a 64.9% success rate in RoboDojo Sim dual-arm robot tests.
## Unitree Robotics integration
Unitree Robotics connected GPT-6 to robots for tasks like painting, without specialized training or complex motion programs.
## UBTech's coordinated approach
UBTech used GPT-6 Astra with dedicated models to complete tasks like stacking bowls, reducing token consumption by 83.6%.
## Google DeepMind's results
Google DeepMind's Gemini Robotics 2.5 achieved a 96% success rate in parts-sorting tests at Mercedes-Benz plants.
## Nvidia's GR00T 2 performance
Nvidia's GR00T 2 achieved a 95% success rate after fine-tuning for 50 new tasks with minimal data.
## Industry shift in robotics
The industry is shifting toward general models handling task understanding while dedicated models manage precision operations.
## Latency and cost challenges
Inference latency for GPT-6 Astra direct-control approaches averages 18.56 seconds per task, with high API costs.
## Key takeaway

OpenAI merged its robotics research into core AI divisions as general-purpose models like GPT-6 Astra demonstrated direct robot control capabilities.