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Engineering Around Silicon Locks: Running LLMs on $130 E-Waste

NVIDIA의 하드웨어 제한을 뚫다: 130달러 '가성비' 채굴 카드로 구현한 LLM 추론 엔진

Why it matters

This technical feat demonstrates how deep software optimization can bypass intentional hardware throttles to repurpose industrial e-waste for high-performance AI. It highlights the potential for 'AI scavenging,' allowing developers to run massive models like Qwen3.5 at a fraction of the cost of modern enterprise GPUs.

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NVIDIA CMP 100-210CUDAQwen3.5Inference EngineGV100HBM2

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