What is MoE? The sparse expert trick behind DeepSeek and Mixtral
Mixture of Experts models run only a fraction of their parameters per token. Here's why DeepSeek and Mixtral are cheap, and when MoE gets expensive.
Tag · fundamentals
Mixture of Experts models run only a fraction of their parameters per token. Here's why DeepSeek and Mixtral are cheap, and when MoE gets expensive.
The exact token-to-word and token-to-character conversion rates for English, code, and non-English LLM input, plus a practical counting recipe.
A 7-step framework for picking the right LLM for any job. Real constraints, real benchmarks, real routing. Stop guessing from leaderboards.
RAG has 3 moving parts: ingestion, retrieval, and generation. Here's what each does, when RAG beats fine-tuning, and when to skip it entirely.
The context window is your LLM's working memory per call. What 128k tokens actually fits, why usable size is smaller than advertised, and how to check yours.