LobeHub(@lobehub):🚨 GLM-5.3-Flash just landed on LobeHub, and the architecture is kind of insane. It has roughly the same total parameter count as GLM-4.5: 355B → 320B total params But under the hood: → Active params: 32B → 18B → Layers: 92 → 45 → 30T-token multimodal pretraining corpus → 1M context window → Native multimodality + tool calling Basically, @Zai_org cut the compute almost in half and somehow made the model stronger. That’s why GLM-5.3-Flash can deliver frontier-level capability at a dramatically lower cost. This is what the next model war looks like: not just bigger models, but much more intelligence per dollar. Now available on LobeHub. ⚡

2026.08.26 16:25

🚨 GLM-5.3-Flash just landed on LobeHub, and the architecture is kind of insane. It has roughly the same total parameter count as GLM-4.5: 355B → 320B total params But under the hood: → Active params: 32B → 18B → Layers: 92 → 45 → 30T-token multimodal pretraining corpus → 1M context window → Native multimodality + tool calling Basically, @Zai_org cut the compute almost in half and somehow made the model stronger. That’s why GLM-5.3-Flash can deliver frontier-level capability at a dramatically lower cost. This is what the next model war looks like: not just bigger models, but much more intelligence per dollar. Now available on LobeHub. ⚡