"How to Tell If an LLM Was Really Trained From Scratch: A Reproducible Fingerprinting Method"

How to Tell If an LLM Was Really Trained From Scratch: A Reproducible Fingerprinting Method

Detect whether an LLM was trained from scratch or derived from Qwen, Llama, or DeepSeek — by fingerprinting architecture, tokenizer, and weight provenance from public Hugging Face artifacts. Includes the two traps almost everyone hits.

Keywords: LLM provenance · model fingerprinting · from-scratch vs fine-tuned · architecture signature · tokenizer overlap · embedding CKA · model lineage · Korean sovereign AI · open-weight derivatives

When a lab announces a "from-scratch, self-developed" foundation model, can an outsider verify that claim — using nothing but public files?

In late July 2026, several Korean labs shipped DeepSeek-rivaling "self-developed" models (e.g. LG's 750B K-EXAONE 2.0). The claim triggered a debate that spilled well beyond Korea: a single Zhihu thread crossed 2.7 million views, asking whether these models were trained from scratch or quietly built on Qwen / Llama / DeepSeek.