• Seattle Skeptics on AI
Seattle Skeptics on AI

Tag: model scaling

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

Tamara Weed, Dec, 20 2025

Parameter count in large language models determines their reasoning power, knowledge retention, and task performance. Bigger isn't always better-architecture, quantization, and efficiency matter just as much as raw size.

Categories:

Science & Research

Tags:

large language models parameter count LLM size model scaling AI capabilities

Recent post

  • Sinusoidal vs Learned Positional Encoding in Transformers: A Guide for LLMs
  • Sinusoidal vs Learned Positional Encoding in Transformers: A Guide for LLMs
  • How AI High Performers Capture Value from Generative AI: Workflow Redesign and Scaling
  • How AI High Performers Capture Value from Generative AI: Workflow Redesign and Scaling
  • How to Use Generative AI for Syllabi, Lesson Plans, and Rubrics
  • How to Use Generative AI for Syllabi, Lesson Plans, and Rubrics
  • Privacy and Security Risks of Distilled LLMs: A Guide for Secure Deployment
  • Privacy and Security Risks of Distilled LLMs: A Guide for Secure Deployment
  • Scaling Open-Source LLMs: Hardware, Serving Stacks, and Playbooks
  • Scaling Open-Source LLMs: Hardware, Serving Stacks, and Playbooks

Categories

  • Enterprise Technology
  • Science & Research

Archives

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

Tags

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

© 2026. All rights reserved.