• Seattle Skeptics on AI
Seattle Skeptics on AI

Tag: transformer compute

Memory and Compute Footprints of Transformer Layers in Production LLMs
Memory and Compute Footprints of Transformer Layers in Production LLMs

Tamara Weed, Feb, 24 2026

Understanding memory and compute footprints in transformer layers is critical for deploying LLMs efficiently. KV cache, quantization, and attention optimizations determine cost, speed, and reliability in production.

Categories:

Science & Research

Tags:

transformer layers LLM memory footprint KV cache inference optimization transformer compute

Recent post

  • State-Level Generative AI Laws in the United States: California, Colorado, Illinois, and Utah
  • State-Level Generative AI Laws in the United States: California, Colorado, Illinois, and Utah
  • Post-Training Evaluation Gates Before Shipping a Large Language Model
  • Post-Training Evaluation Gates Before Shipping a Large Language Model
  • Parameter Counts in Large Language Models: Why Size and Scale Matter for Capability
  • Parameter Counts in Large Language Models: Why Size and Scale Matter for Capability
  • Structured Reasoning Modules in Large Language Models: How Planning and Tool Use Boost Accuracy
  • Structured Reasoning Modules in Large Language Models: How Planning and Tool Use Boost Accuracy
  • How Usage Patterns Affect Large Language Model Billing in Production
  • How Usage Patterns Affect Large Language Model Billing in Production

Categories

  • Science & Research

Archives

  • February 2026
  • January 2026
  • December 2025
  • November 2025
  • October 2025
  • September 2025
  • August 2025
  • July 2025

Tags

vibe coding large language models AI coding tools prompt engineering generative AI LLM security AI governance AI coding AI compliance transformer models AI code security GitHub Copilot LLM deployment AI agents AI implementation data privacy AI development LLM architecture GPU optimization AI in healthcare

© 2026. All rights reserved.