Article • 22 days ago

Understanding GPU Memory Requirements for Large Language Models (LLMs)

Spheron

Summary

LLMs heavily rely on GPU resources for inference, with memory consumption divided into model parameters, KV cache, activations, and overheads.
Techniques like PagedAttention and vLLM revolutionize GPU memory optimization by reducing fragmentation and dynamically allocating memory.

Source: https://blog.spheron.network/how-much-gpu-memory-is-required-to-run-a-large-language-model-find-out-here

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