To train generalist robot policies, machine learning methods often require asubstantial amount of expert human teleoperation data. An ideal robot forhumans collecting data is one that closely mimics them: bimanual arms anddexterous hands. However, creating such a bimanual teleoperation system withover 50 DoF is a significant challenge. To address this, we introduce Bidex, anextremely dexterous, low-cost, low-latency and portable bimanual dexterousteleoperation system which relies on motion capture gloves and teacher arms. Wecompare Bidex to a Vision Pro teleoperation system and a SteamVR system andfind Bidex to produce better quality data for more complex tasks at a fasterrate. Additionally, we show Bidex operating a mobile bimanual robot for in thewild tasks. The robot hands (5k USD) and teleoperation system (7k USD) isreadily reproducible and can be used on many robot arms including two xArms(16k USD). Website at https://bidex-teleop.github.io/