Benchmark Almanac

BEHAVIOR Challenge 2025

Robot Learning Collective (BEHAVIOR 2025 team) 26% tops its leaderboard
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50 long-horizon household activities on a Galaxea R1 Pro in OmniGibson, trained from 10,000 demos. Scored by Q-score and success.

Far from saturated: winning held-out Q-score 0.26, full-task success 12.4%. Scores teams, not models. 2026 edition adds pi0.5 and GR00T N1.7 baselines. Results due November 4th, 2026.

Released
September 2025
Kind
Simulated robots
Level
Everyday
Scored
Checked automatically
Answers
Agent task
Tasks
Public, plus a private test set
Last in a launch post
December 2025, dropped before it saturated
Last model added
December 2025

In the authors’ words

We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered robotics. BEHAVIOR-1K includes two components, guided and motivated by the results of an extensive survey on "what do you want robots to do for you?". The first is the definition of 1,000 everyday activities, grounded in 50 scenes (houses, gardens, restaurants, offices, etc.) with more than 9,000 objects annotated with rich physical and semantic properties. The second is OMNIGIBSON, a novel simulation environment that supports these activities via realistic physics simulation and rendering of rigid bodies, deformable bodies, and liquids. Our experiments indicate that the activities in BEHAVIOR-1K are long-horizon and dependent on complex manipulation skills, both of which remain a challenge for even state-of-the-art robot learning solutions. To calibrate the simulation-to-reality gap of BEHAVIOR-1K, we provide an initial study on transferring solutions learned with a mobile manipulator in a simulated apartment to its real-world counterpart. We hope that BEHAVIOR-1K's human-grounded nature, diversity, and realism make it valuable for embodied AI and robot learning research. Project website: https://behavior.stanford.edu.

Abstract of BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation (arXiv:2403.09227, CC0)
5
Entries on its own leaderboard, 0 models we track
1
Launch post lists it, from 1 lab

Robot Learning Collective (BEHAVIOR 2025 team) tops the leaderboard with 26%

Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.

  1. 1 Robot Learning Collective (BEHAVIOR 2025 team) Standard 26%
  2. 2 Comet (BEHAVIOR 2025 team) Standard 25.1%
  3. 3 SimpleAI Robot (BEHAVIOR 2025 team) Standard 15.9%
  4. 4 The North Star (BEHAVIOR 2025 team) Standard 12%
  5. 5 Embodied Intelligence (BEHAVIOR 2025 team) Privileged 9.47%

Source: Official BEHAVIOR Challenge 2025 leaderboard

#EntryScoreSettingDateSource
1 Robot Learning Collective (BEHAVIOR 2025 team) 26% Standard Nov 2025 Official leaderboard
2 Comet (BEHAVIOR 2025 team) 25.1% Standard Nov 2025 Official leaderboard
3 SimpleAI Robot (BEHAVIOR 2025 team) 15.9% Standard Nov 2025 Official leaderboard
4 The North Star (BEHAVIOR 2025 team) 12% Standard Nov 2025 Official leaderboard
5 Embodied Intelligence (BEHAVIOR 2025 team) 9.47% Privileged Nov 2025 Official leaderboard

Labs headline it less often now, last in December 2025

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

NVIDIA
DateLaunch postScoreAs the post writes it
Dec 16, 2025 GR00T N1.6 BEHAVIOR 50 tasks on the R1 Pro, average Task Progress 26.30% (π0.5 11.30%), a denser metric than the challenge Q score (examples/BEHAVIOR README)

Versions

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