RAX 机器人 agent 接入 V4.1 Flash：DexJoCo 超 π0.5 逾 10%，成本约 Opus 5.
RAX 支持 DeepSeek Harness 与自托管 V4.1 Flash，仅 3 个示范就在 DexJoCo 上比 π0.5、Fast-WAM 高 10% 以上，API 价格约为 Opus 5.5 的二十分之一。
🚀 RAX now supports DeepSeek Harness and Kimi Code as agent harnesses! We’ve also added direct support for self-hosted DeepSeek-V4.1-Flash, so you can run RAX with local inference. On the DexJoCo benchmark, RAX + DeepSeek-V4.1-Flash outperforms π0.5 and Fast-WAM by more than 10% with just 3 demonstrations. At API pricing, it costs roughly 1/20 as much as Claude Opus 5.5! Try it out! 🤖 🌐 Project + sessions: https://robot-agent-exploration.com 📄 Paper: https://arxiv.org/abs/2610.22496 💻 GitHub: https://github.com/robot-agent-exploration/rax 🧩 Skill library: https://github.com/robot-agent-exploration/skills-lib 🤗 Dataset with full robot logs and sessions: https://huggingface.co/datasets/robot-agent-exploration/robot-session-logs @deepseek_ai @Kimi_Moonshot #Robotics #EmbodiedAI #AIAgents #OpenSource #DeepSeek #RobotLearning #LLM
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