Engram Embeddings: Caching Multi-Word Semantics for Cheaper, Smarter Models

Engram embeddings cache multi-word semantic combinations, saving compute while boosting model intelligence. The approach overlaps embedding loading with GPU computation for near-zero retrieval cost, and reportedly beats GLM 5.3 with a smaller KV cache despite comparable total weights.

2026-09-10 ~ 2026-09-10 · 3 related posts

• Engram embeddings load overlapped with GPU compute, so fetch time costs nothing — bookwormengr · 2026-09-10
• Engram embeddings: caching multi-token meanings to cut compute and boost intelligence — bookwormengr · 2026-09-10
• Engram architecture explained: 500B backbone beats GLM 5.3-class with far smaller KV cache — bookwormengr · 2026-09-10