AINewsnow

Mixture of Experts (MoE): Why Big AI Models Are Cheaper to Run Than They Look

This story is from 2026-09-21. It is preserved in the archive; the latest stories are on the live feed.

DeepSeek-V3 has 671 billion parameters. When it processes your prompt, it uses about 37 billion of them per token. The rest sit idle. That is not a typo, and it is not a trick. It is an architecture called Mixture of Experts, or MoE. Once you understand it, a lot of confusing things about modern AI…

Read the full story at DEV Community — Machine Learning ↗

Timeline · 1 report

  1. 2026-09-21 07:21 · DEV Community — Machine Learning
    Mixture of Experts (MoE): Why Big AI Models Are Cheaper to Run Than They Look

More stories

  1. Bolt Adds DeepSeek V4.1 Flash at 10x Cheaper Than V4 Pro — AlphaSignal
  2. DeepSeek’s Insane New Architecture — Two Minute Papers
  3. Gemini 4 is good enough - JUST RELEASE IT — r/GeminiAI
  4. Foulmouth Qwen 3.8 27b, an unexpected thought process... — r/LocalLLaMA
  5. Is there any use of a local llm with a 20B LLM? — r/AI_Agents
  6. Ai used for chatbots — r/artificial
  7. I gave 6 different AIs the same 5 questions — r/AI_Agents
  8. PromptDeck v1.1.0 – open-source desktop app to benchmark local AND cloud LLMs side-by-side (Ollama, LM Studio + OpenRouter, Groq, DeepSeek…) — r/LocalLLaMA

Get the daily brief of stories like this at 6:30 every morning →