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    Guava open-sourced to turn frontier AI into compact robot agents

    Its developers report 90.0% real-world success for Guava-4B, versus 93.3% for GPT-5.4.

    Furong HuangFH
    Xirui LiXL
    2 Sources, ,

    TLDR

    Guava’s developers say they open-sourced a framework for distilling frontier models into compact robot agents using only simulation interaction data. They say they fine-tuned Qwen3.5 into Guava-4B with about 2,000 simulation trajectories and report 90.0% real-world success, versus 93.3% for GPT-5.4, with 7.1× lower model-call latency through local inference.

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    Combined views

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    2 Sources, first seen 3h ago

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    2 Sources

    Xirui Li@xiruili7_li🤖 Frontier models like GPT 6 Astra are getting surprisingly good at controlling robots. The results are exciting, but deploying frontier models on robots comes with substantial inference cost and latency. Can we distill these capabilities into compact models that run locally? We open-source 🥑Guava — a framework for distilling frontier models into compact robot agents, using purely simulation interaction data, no real-world data required! With only ~2K simulation trajectories, we finetuned Qwen3.5 into Guava-4B, with: 🤖 90.0% real-world success vs. 93.3% for GPT-5.4 ⚡ 7.1× lower model-call latency with local inference 🌎 Sim-to-real transfer without real-world fine-tuning 🧠 Generalization to unseen tasks and object configurations 🔄 Closed-loop recovery from execution failures Paper + code + project page: https://guava-harness.github.io/ 🎥 See Guava in action below. Joint efforts from @haowenssr, @xiruili7_li, @ShaoxiongYao, Peng Shi, @zhoutianyi, @jbhuang0604 , @furongh and @maojiayuan.3h
    Furong Huang@furonghRT @xiruili7_li: 🤖 Frontier models like GPT 6 Astra are getting surprisingly good at controlling robots. The results are exciting, but depl…1h

    2 Sources

    Xirui Li@xiruili7_li🤖 Frontier models like GPT 6 Astra are getting surprisingly good at controlling robots. The results are exciting, but deploying frontier models on robots comes with substantial inference cost and latency. Can we distill these capabilities into compact models that run locally? We open-source 🥑Guava — a framework for distilling frontier models into compact robot agents, using purely simulation interaction data, no real-world data required! With only ~2K simulation trajectories, we finetuned Qwen3.5 into Guava-4B, with: 🤖 90.0% real-world success vs. 93.3% for GPT-5.4 ⚡ 7.1× lower model-call latency with local inference 🌎 Sim-to-real transfer without real-world fine-tuning 🧠 Generalization to unseen tasks and object configurations 🔄 Closed-loop recovery from execution failures Paper + code + project page: https://guava-harness.github.io/ 🎥 See Guava in action below. Joint efforts from @haowenssr, @xiruili7_li, @ShaoxiongYao, Peng Shi, @zhoutianyi, @jbhuang0604 , @furongh and @maojiayuan.3h
    Furong Huang@furonghRT @xiruili7_li: 🤖 Frontier models like GPT 6 Astra are getting surprisingly good at controlling robots. The results are exciting, but depl…1h