A structured learning framework now exists to dissect new open-weight model releases. It prioritizes technical documentation and architectural benchmarks over marketing claims. This systematic approach helps AI researchers isolate specific model improvements. Practitioners can use this method to evaluate if a new LLM architecture justifies the migration cost for their specific use case.