Multiverse Computing proposes Quantization-Aware Healing: 4-bit compressed model beats its bfloat16 original on seven of nine benchmarks
Quantization-Aware Healing: a compressed, 4-bit model that outperforms its full-precision original
What happened
Multiverse Computing has published a paper proposing Quantization-Aware Healing (QAH). After compressing GPT-OSS 120B to 60B parameters and quantizing it to MXFP4, the method distills directly from the original model before compression rather than from a recovered bfloat16 checkpoint.
Why it matters
The paper presents a repair recipe that distills from the original model after compression and quantization, with stability comparisons against QAT.
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