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Been playing around with both of these since last night. So far, when enabling reasoning (which is binary on/off), it seems to me like Flash either is less "token efficient" or just likes to think more, or I'm doing something else wrong, because most prompts I send to both, Flash reasons more and for longer than Pro, which is the opposite of my expectations.

Are others seeing the same thing?

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Most of the Chinese models get into long complicated thinking loops before they accomplish something more complicated.

This is also true for Deepseek 4(.1) .

Any lower (or broken) quantization could do that, not what I'm talking about though. They work fine for their size, as far as I can tell. Just surprised the Flash would reason for longer than the Pro.

I prefer GLM 5.3 (Flash or not) over Deepseek 4.1 Flash because the GLM models are significantly less verbose.

Maybe it’s the quant you’re using?

Tried both https://token-plan-ams.xiaomimimo.com/v1 and https://api.xiaomimimo.com/v1, hoping they don't run any quantized variants there, but who knows.

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