SteerDistill for Quantization-Aware Agent Distillation
November 9, 2026
SteerDistill uses a full-precision teacher to guide quantized agents through a closed-loop process. The method identifies where quantized models diverge from successful references and uses iterative feedback to correct behavioral failures during execution.
HOW THIS AFFECTS YOU
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builderYou can reduce inference costs with low-bit quantization while maintaining agent task success rates.