GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2
A benchmark comparison found that GPT-5.5 hallucinates three times more frequently than the MIT-licensed GLM-5.2 model, highlighting significant differences in factual reliability between the two large language models.
Background
- The post appears to compare two large language models: a hypothetical "GPT-5.5" (presumably referring to OpenAI's GPT series) and "GLM-5.2," which is a model from the GLM family developed by Tsinghua University and Zhipu AI (a Chinese AI company). GLM models are known for being open-source under permissive MIT licenses, unlike OpenAI's proprietary models.
- The claim that an MIT-licensed model (GLM-5.2) hallucinates less than a much larger proprietary model (GPT-5.5) challenges the prevailing assumption that bigger models always perform better. It suggests that architectural choices, training data quality, and licensing openness can matter more than raw scale.
- Hallucination—when a model generates plausible-sounding but false or nonsensical information—remains a critical weakness of LLMs. Comparisons like this are significant for developers deciding which model to build applications on, and for debates about open vs. closed AI development.