How Grouped-Query Attention (GQA) and Multi-Query Attention (MQA) reduce KV-cache memory bandwidth consumption in LLM inference.
Standard Multi-Head Attention (MHA) maintains $H$ distinct Key and Value heads. Grouped-Query Attention (GQA) shares KV heads across query head groups, yielding 8x memory bandwidth reduction during generation.
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Principal AI Architect. Former DeepMind Researcher specializing in Large Language Models and Prompt Engineering.