Unverified50% confidenceFactExact time
Zhipu did not retrain the model base, but retained GLM-5.2's base and only expanded and reinforced it during the post-training phase.
1
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50%
Confidence
Long-term
Relevance
9/12/2026
First Seen
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Related Claims
UnverifiedZhipu GLM 5.2 only releases post-training weights rather than the base model, in order to strike a balance between open source and commercial licensing.75% similarVerifiedThe GLM series originally adopted an autoregressive blank-filling pre-training framework that accommodates both understanding and generation capabilities.72% similarUnverifiedWhen the initial model is trained for only 5 epochs, the recognition effect is limited67% similarVerifiedAfter LoRA training is complete, the low-rank matrices can be merged back into the original weights, introducing no additional latency during inference.67% similarUnverifiedOther residual connection improvement schemes outperform the original version in the early stages of training but fall behind the original version in the later stages.66% similar
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