Multiverse Computing Claims a 4-Bit Compressed Model Beats Its Full-Precision Original, and r/LocalLLaMA Is Not Buying It

Hugging Face blog (Multiverse Computing), via r/LocalLLaMA·low signalXBlueskyLinkedInCopy link

Multiverse Computing published a Hugging Face blog on 'Quantization-Aware Healing', claiming a compressed 4-bit model outperforms the full-precision original. The thread's technical readers took it apart within hours: one notes GPT-OSS was trained in 4 bits from the start so the framing is confused, another clarifies the actual claim is a 120B cut to a 60B BF16 model, then to 60B mxfp4 that beats the 60B BF16 but not the 120B base. The strongest critique comes from the Heretic author, who accepts KLD against the teacher distribution as a good loss function but argues first-token KLD poorly predicts divergence over a full response.