A 2-billion-parameter small-model surpasses NVIDIA’s flagship model. Shanghai’s “World Model” tops an internationally recognized authoritative leaderboard with a “direct entry” (“no special preparation” / no special handling).

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ME AI News, from ZhiYuan Robot, the self-developed world model Genie Envisioner-Sim 2.0 (abbreviated as GE 2.0) has achieved excellent overall performance, ranking first on the global world model evaluation benchmark World Arena's "Perception and Action Response" leaderboard. This time, ZhiYuan's GE 2.0 participated in the "Perception and Action Response" track evaluation, directly competing with top domestic and international AI teams such as NVIDIA's latest model DreamDojo and the Ctrl-World team jointly developed by Tsinghua University and Stanford, ultimately winning the championship. According to disclosed technical documents, GE 2.0, a model with only 2 billion (2B) parameters, outperformed flagship models with ultra-large parameters from NVIDIA, Microsoft, and others, also demonstrating that lightweight models are not inferior to ultra-large parameter models in humanoid robot applications. (Shanghai Observer News) (Source: Tonghuashun)
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FiveMinutesBeforeLiquidation
· 5h ago
NVIDIA has actually been overtaken by 2B parameters; maybe it's time to rethink the parameter arms race.
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FeeswitchWhisperer
· 9h ago
Winning with a lightweight model shows that algorithm architecture matters far more than brute-force parameter stacking.
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NotificationSoundInMistyValley
· 9h ago
2B vs tens of billions, this efficiency gap is a matter of life and death on the edge side
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Re-StakingSucculents
· 10h ago
The key to humanoid robots hitting the ground is the world model; this track will become increasingly competitive.
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SudoSoul
· 10h ago
Perception and Action Response Track, in simple terms, is the robot version of "see and act."
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StakingDaydreamer
· 10h ago
Is the Ctrl-World team the one that came out of MIT—getting shredded by the 2B parameter?
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MountainBeforeTheStorm
· 10h ago
Have you heard of the World Arena benchmark before? Does anyone knowledgeable want to give a quick explanation?
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