APEX is a quantization strategy for Mixture-of-Experts (MoE) models. It classifies tensors by role (routed expert, shared expert, attention) and applies a layer-wise precision gradient -- edge layers get higher precision, middle layers get more aggressive compression. I-variants use diverse imatrix calibration (chat, code, reasoning, tool-calling, agentic traces, Wikipedia).
See the
APEX project
for full details, technical report, and scripts.
Architecture
Model
: GLM-4.7-Flash (Glm4MoeLite)
Layers
: 47 (1 dense + 46 MoE)
Experts
: 64 routed + 1 shared (4 active per token)
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