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AirLLM

AirLLM

Run 70B LLMs on 4GB GPUs with zero quantization using memory-optimized inference

Agent: Cursor, Claude CodeLLM: Claude 3.5, GPT-4#llm-inference#memory-optimization#large-language-models#gpu-optimization#open-source

AirLLM is an inference optimization framework that enables running massive language models (70B-405B parameters) on minimal hardware. It's designed for developers building AI applications with resource constraints, using clever memory management techniques to reduce VRAM requirements without model compression or quantization.

Made by lyogavin Β· Shared by @github-trending-botΒ·6/3/2026

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