Benchmark Almanac

Gemini Robotics generalization benchmark

Not in model cards

Robot policies run 85 real bi-arm manipulation tasks. About 80% test generalization to new scenes, new wording of instructions or new actions. Scored by average progress and success rate.

Of the 85 tasks, 20% are in distribution, 28% visual, 28% instruction and 24% action generalization. The Gemini Robotics On-Device cards report scene, instruction and action generalization in the same way.

Made by Google DeepMind Released Mar 2025 Real robots Tasks kept private
Level
Everyday Most adults, without training
Scored
Settled by events Predictions are scored against what later happens.
Answers
Agent task Many steps in a terminal, browser, desktop, app, game or robot.

No scores here yet

No lab, leaderboard or Epoch AI run has reported a score for Gemini Robotics generalization benchmark yet.

No lab model card reports it yet

We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark.

More in Robotics

All 86 in Robotics
  • ERQA In use 400 multiple-choice visual questions from robot and egocentric footage on spatial, trajectory, action and state reasoning. Accuracy. Gemini Robotics ER 2 78.5%
  • RoboLab In use Zero-shot DROID Franka policies in Isaac Lab on 120 tabletop tasks at three instruction levels, 10 episodes each. Success rate. GR00T N1.7 8.58%
  • Human proximity (Google DeepMind robotics) In use Models judge from robot camera views whether a human is within 1 meter, a spatial awareness check for safe robot behavior. Scored by accuracy. Gemini Robotics ER 2 93%
  • Moment finding (Google DeepMind) In use Models find the moment in a robot video when an event happens. Scored by accuracy and mean absolute time distance in seconds. Gemini Robotics ER 2 91.3%
  • Progress classification (Google DeepMind) In use Models assign each frame of a robot video to one of five task-progress bands from 0 to 100 percent. Scored by accuracy. Gemini Robotics ER 2 57.4%
  • LIBERO Fading Simulated Franka tabletop tasks in four 10-task suites. Policies fine-tuned on 50 demos per task. Success rate over ~50 trials. MolmoAct 2 97.2%