TREE NEWS update: Zhiyuan’s GO-3 Nano Preview ranked first on the latest RoboDojo embodied intelligence benchmark with an average score of 61.90 and an average success rate of 56.42%, surpassing GPT-6 Astra. The model scored 78.65 in fine manipulation, 68.21 in long-horizon execution and 61.71 in open semantic understanding.
Zhiyuan’s GO-3 Nano Preview Tops RoboDojo Benchmark, Beats GPT-6 Astra
The headline is the ranking, but the sub-scores are the real story: strength in fine manipulation alongside a weaker open semantic understanding suggests a model optimized for controlled tasks rather than general-purpose reasoning in messy environments. That gap matters for anyone building embodied systems where perception and language grounding are the bottleneck. A single benchmark lead over GPT-6 Astra is a snapshot, not a durable position, and preview-stage results leave open whether the margin holds once the model ships and rivals iterate. Watch whether the semantic-understanding deficit narrows in subsequent evaluations.
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