4-bit quantization has become the de facto standard for running LLMs on consumer hardware - a 70B model drops from ~140G...

4-bit quantization has become the de facto standard for running LLMs on consumer hardware - a 70B model drops from ~140GB to ~35-40GB, and kernels like Marlin push inference close to a theoretical 4x speedup. But accuracy loss isn't uniform: general chat tasks barely budge, while coding and reasoning benchmarks have shown drops as steep as 7-14 percentage points under aggressive settings.https://psyll.com/articles/technology/ai-machine-learning/4-bit-quantization-the-real-trade-offs-explained#ai #llm