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AirLLM claims you can run 70B models on consumer GPUs with just 4GB VRAM. Here's how it works, where it breaks, and whether it's actually useful for real workloads.

Under the hood of post-training quantization. Learn how mapping FP16 weights to INT4 shrinks LLMs, reduces memory bandwidth, and enables local AI execution.