AI Engineer · August 7, 2026

Compression at the Edge — NVIDIA, Unsloth, HuggingFace, Ollama

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Why it matters

Quantize a single number in a model and it gets 20% dumber. That finding, from the super weights paper, is why Daniel Han's claim is less absurd than it sounds: GLM 5.2 goes from 1.5 terabytes to 250 GB, 86% smaller, without being 86% dumber. Layers are wildly unequal.

My takeaway: Compression at the Edge — NVIDIA, Unsloth, HuggingFace, Ollama is a model-evaluation signal. The practical read is to tie capability claims to evidence, launch criteria, and regression tests rather than relying on demos or benchmark headlines.

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