If you are running quantized LLMs locally, especially 4-bit models, memory bandwidth usually matters more than raw CUDA core count. Once the model fits in VRAM, inference speed is largely determined by how fast the GPU can stream weights from VRAM into the tensor cores. For 7B models this is less obvious. For 34B, 70B, the bandwidth becomes one of the main bottlenecks. This a...
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