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Figure 57: GLM-4.7 355B · diagram by Sebastian Raschka · click to zoom
Sparse MoEZ.ai 🇨🇳 · December 22, 2025

GLM-4.7 (355B)

Immediate GLM predecessor that stays closer to the older GLM-4.5 style before the MLA shift.

Key detail

Serves as the pre-MLA, pre-sparse-attention baseline and uses an MTP-3-style setup.

Total params

355B

Active / token

32B

Context

198K

Fact sheet

Scale
355B total, 32B active (9% active)
Context window
202,752 tokens
Decoder type
Sparse MoE
Attention
GQA with QK-Norm
Layer mix
92 GQA
KV cache / token (bf16)
368 KiB · Very high
License
MIT License
Released

Efficiency

Parameters active per token

9.0%

32B of 355B weights run for each token.

KV cache per token (bf16)

368 KiB

Smaller than 6% of models in the atlas. How it’s calculated

AA Intelligence Index v4.3.2

Source

17.4

Scientific
3.2

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Similar architectures

  • Architecture diagram of GLM-4.5 (355B)

    Z.ai, released 2025-07-28. Sparse MoE decoder, 355B total, 32B active, 128K context. Attention: GQA with QK-Norm.

  • Architecture diagram of MiniMax M2 (230B)

    MiniMax, released 2025-10-23. Sparse MoE decoder, 230B total, 10B active, 192K context. Attention: GQA with QK-Norm and partial RoPE.

  • Architecture diagram of MiniMax-M2.5 (230B)

    MiniMax, released 2026-02-12. Sparse MoE decoder, 230B total, 10B active, 192K context. Attention: GQA with QK-Norm.

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