🚀HardInference OptimizationPREMIUM

Multi-Query & Grouped-Query Attention

Master the inference optimizations that make serving large models possible. Compare MHA, MQA, and GQA architectures and their impact on KV cache memory.

What you'll master

Multi-Head Attention (MHA) memory bottlenecks

Multi-Query Attention (MQA) shared KV projections

Grouped-Query Attention (GQA) architecture

KV cache memory bandwidth vs capacity

Uptraining MHA checkpoints to GQA

Throughput vs Latency tradeoffs

Tensor Parallelism constraints for KV heads

Multi-Head Latent Attention (MLA) compression

Hard25 min readIncludes code examples, architecture diagrams, and expert-level follow-up questions.

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Code examplesArchitecture diagramsModel answersScoring rubricCommon pitfallsFollow-up Q&A

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