Inside 4 Frontier Efficient Architectures: DeepSeek, Qwen, GLM, MiMo Compared
eliebakouch · x · 2026-09-24
A technical thread compares the 4 most advanced efficient architectures: DeepSeek V4.1 Flash, MiMo V3, Qwen 3.8 Next Flash, and GLM 5.3 Flash (visualization co-created with Opus 5.5).
Two camps:
- DeepSeek & MiMo: both use YOCO — only the first part of the network is active during prefill to build the KV cache, no linear attention, token-level indexer.
- Qwen & GLM: standard 3:1 interleaving (like Kimi K3) between sparse attention and linear attention (GDN vs KDA).
Shared details: DeepSeek and Qwen both use Engram; all use a gate or sink except GLM 5.3 Flash; all use no or partial RoPE on full/sparse attention layers; all feature sophisticated residual networks (simplified/full mHC or gated residual); all trained with Muon.
Related event: DeepSeek, Qwen, GLM, and Xiaomi Efficient Architectures Compared(2 posts)→
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