TinyAstral Distills Large Teacher Harnesses into Small Agents
October 29, 2026
TinyAstral uses recursive self-improvement to evolve a large teacher's harness before distilling its reasoning and recovery capabilities into a compact student agent. This process significantly raises success rates on the RoboTwin benchmark.
HOW THIS AFFECTS YOU
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builderYou can use this to deploy high-performing, low-cost manipulation agents in resource-constrained environments.
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researcherThis demonstrates how harness evolution can be transferred from frontier models to small agents.