llms-explained

3 posts

LLMS EXPLAINED · 02189 GiB OF N-GRAM MEMORY12.4 KiBREAD PER TOKEN

Engram: Memory You Look Up Instead of Compute

DeepSeek's Engram adds a hashed n-gram memory that a model looks up instead of computing: how it works, why it helps, and how DeepSeek-V4.1 and Qwen serve it.

LLMS EXPLAINED · 0348 LAYERS · 3 LINEAR : 1 SPARSE1/9TRAINING FLOPS

Qwen3.8-Flash-Next, Layer by Layer

Qwen's preview of its next architecture, piece by piece: linear and sparse attention, a gated four-branch residual, 512 experts and an n-gram memory, and what each costs to serve.

LLMS EXPLAINED · 0183%ON THE TOP WORDTHE TEACHER'S NEXT-TOKEN DISTRIBUTION

Distillation: How Small Models Learn from Big Ones

What distillation is, the ways labs distill models, and how they use it on their own models and on others', from primary sources.