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GLM 5.3's gains came entirely from post-training the previous model

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Z.ai's GLM 5.3 was built entirely by post-training its predecessor, GLM 5.2, without pretraining from scratch.

A quoted speaker says post-training is far more GPU-efficient than pretraining, letting firms with proprietary data improve models without the cost of training from scratch.

The same speaker says GLM 5.3's cyber capabilities are dramatically better than 5.2's, all from post-training.

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GLM 5.3’s biggest leap came from post-training alone.

“GLM 5.3 was built entirely by post-training the previous model. For me, that was a wake-up call.”

“Post-training is far more GPU-efficient than pre-training from scratch. Plenty of companies can’t afford to train a model from scratch, but they have proprietary data. They can post-train themselves and beat some of the closed models.”

“There’s still so much juice left to squeeze from post-training. We compared GLM 5.3’s cyber capabilities with 5.2, and it’s a night and day difference. That’s all just post-training.”

Source: SemiAnalysis · x.comPublished · added here