Techniquesmodel architecturecontext capacity

implementation detail · filed under model architecture

Single-layer N-gram embedding placement

An implementation that uses one N-gram embedding layer, placed at layer 2 in the cited evidence.

Also called A single N-gram embedding layer.

source: 1
model: 1
lab adopt it: 1
strongest: core

How sources treat it

One count per evidence span, weakest treatment to strongest.

core 1

Documented in

Qwen3.8-Flash-Next

Evidence

1 span quoted from the sources, strongest treatment first.

A single N-gram embedding layer is sufficient. ... We place it at Layer 2

coremodel architecturein Qwen3.8-NextQwen

On the Design of Qwen3.8-Next Architecture: Evaluation, Efficiency, and Training Stability·Qwen·2026-08-31

Filed alongside

Other methods under model architecture :: context capacity.

N-gram embedding host-memory offload and prefetch N-gram embedding lookup Engram 1M-token context window Progressive context extension 256K context window Multi-head hashing Row-wise distributed partitioning of embedding tables Token normalization for N-gram vocabulary compression