Reasoning models generate very long chains of reasoning, so even small quantization errors accumulate over time.

With AWQ, the Qwen3-4B result on MMLU-Pro drops from 71.0 to 68.2 (about a 4% relative decline).
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ParoQuant fixes this! It only retains critical rotation pairs and combines everything into a single kernel.

It recovers most of the lost accuracy in reasoning tasks with minimal overhead, so 4-bit models remain strong in reasoning tasks.
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Accepted at ICLR 2026

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