• Seattle Skeptics on AI
Seattle Skeptics on AI

Tag: LLM serving

How to Choose Batch Sizes to Minimize Cost per Token in LLM Serving
How to Choose Batch Sizes to Minimize Cost per Token in LLM Serving

Tamara Weed, Nov, 24 2025

Learn how to choose batch sizes for LLM serving to cut cost per token by up to 87%. Real-world examples, optimal batch sizes, GPU limits, and proven cost-saving techniques.

Categories:

Science & Research

Tags:

batch size LLM serving cost per token GPU utilization LLM optimization

Recent post

  • Trustworthy AI for Code: How Verification, Provenance, and Watermarking Are Changing Software Development
  • Trustworthy AI for Code: How Verification, Provenance, and Watermarking Are Changing Software Development
  • Prompting LLMs for Code: Proven Patterns for Unit Tests and Refactors
  • Prompting LLMs for Code: Proven Patterns for Unit Tests and Refactors
  • Federated Learning for Generative AI: How to Collaborate Without Sharing Data
  • Federated Learning for Generative AI: How to Collaborate Without Sharing Data
  • Domain Adaptation for LLMs: Medical, Legal, and Finance Guide
  • Domain Adaptation for LLMs: Medical, Legal, and Finance Guide
  • Build vs Buy for Generative AI Platforms: Decision Framework for CIOs
  • Build vs Buy for Generative AI Platforms: Decision Framework for CIOs

Categories

  • Enterprise Technology
  • Science & Research

Archives

  • October 2026
  • September 2026
  • August 2026
  • July 2026
  • June 2026
  • May 2026
  • April 2026
  • March 2026
  • February 2026
  • January 2026
  • December 2025
  • November 2025

Tags

vibe coding prompt engineering large language models generative AI transformer architecture LLM security AI governance Large Language Models prompt injection data privacy AI coding tools AI development responsible AI LLM optimization AI compliance AI code generation LLM architecture software architecture multimodal generative AI transformer models

© 2026. All rights reserved.