新论文在 12 个机器人基准上测试 GPT-6-Astra
GPT-6-Astra 机器人基准测试新论文
一篇新论文在 12 个机器人基准上测试 GPT-6-Astra，该模型在 LIBERO 套件接近饱和，在 RoboDojo 达 81.9%、DexJoCo 达 87.3%。
Rohan Paul· @rohanpaul_ai · X·2026-10-22 13:56· 19 分钟前AI 评分45
AI 导读
新论文测试 GPT-6-Astra 在 12 个机器人基准上的表现，其在 LIBERO 套件接近饱和，RoboDojo 达 81.9%、DexJoCo 达 87.3%，但无法验证物理成功或从不可逆错误中恢复。
正文 · 原文
New paper finds that GPT-6-Astra nearly saturates easy robot benchmarks but still fails to verify physical success and recover from irreversible mistakes.
And at a cost too high for real use.
Robot manipulation and navigation have been dominated by task-specific models. The question was whether 1 general model could handle them all without weight updates.
The authors tested GPT-6-Astra on 12 robot benchmarks. It studied training demos into a frozen knowledge package and got up to 10 times the usual action steps to recover.
It neared saturation on the LIBERO suite and reached 81.9% on RoboDojo and 87.3% on DexJoCo. But a single LIBERO-Ultra-Long episode used about 9M tokens and nearly 2 hours, and on real robots it could not trade more steps for success.
Treat general models as capable robot controllers for research, but expect task-specific demos, heavy compute, and physical limits to block deployment for now.
– arxiv. org/abs/2610.22471
Title: "Has GPT-6-Astra Achieved Embodied Intelligence?"
来源：Rohan Paul · x.com
来源：RadarAI · aihot.news