3T is impressive, but parameter count seems to be less important than I thought.

GLM is half the size of DeepSeek but costs four times as much, and beats it on every benchmark.

I'm not an expert on this stuff but it seems to be the attention mechanism. DeepSeek were bragging about how cheap they made it. But if you cut costs on attention you get worse results with way more parameters.

If I had to guess it seems to be the difference between memory (params) and intelligence (attention density). I think you need both.

After MoE entered the mix, raw parameter count is less useful a measure.

Or, GLM 5.2 simply had more time in the RL oven.

Deepseek V4 Flash, the 284B model, is roughly equivalent to launch GLM 5, the 744B [sic] model.