• 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

  • Chain-of-Thought Prompting: A Step-by-Step Guide to Complex AI Reasoning
  • Chain-of-Thought Prompting: A Step-by-Step Guide to Complex AI Reasoning
  • Transformer Architecture Explained: A Technical Deep Dive into LLMs
  • Transformer Architecture Explained: A Technical Deep Dive into LLMs
  • Sparse Attention and Performer Variants: Efficient Transformer Ideas for LLMs
  • Sparse Attention and Performer Variants: Efficient Transformer Ideas for LLMs
  • Ethical AI Agents for Code: Guardrails that Enforce Policy by Default
  • Ethical AI Agents for Code: Guardrails that Enforce Policy by Default
  • Domain-Specialized Generative AI Models: Why Industry-Specific AI Outperforms General Models
  • Domain-Specialized Generative AI Models: Why Industry-Specific AI Outperforms General Models

Categories

  • Enterprise Technology
  • Science & Research

Archives

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

Tags

vibe coding prompt engineering large language models generative AI transformer architecture LLM security AI governance Large Language Models data privacy prompt injection AI coding tools responsible AI AI compliance LLM optimization transformer models AI development AI coding assistants LLM evaluation LLM-as-a-Judge multimodal generative AI

© 2026. All rights reserved.