GPT-5.5 HALLUCINATES 3X MORE THAN OPEN GLM-5.2

Recent benchmarking shows GPT-5.5 generates false or unsupported information significantly more often than its open-source competitor GLM-5.2, according to testing published on ArrowTSX. The proprietary model's hallucination rate stands at 3x that of the MIT-licensed alternative. Hallucinations—instances where AI systems generate plausible-sounding but factually incorrect information—remain a persistent challenge in large language models. The disparity suggests that scale alone does not guarantee reliability, and that architectural or training choices impact accuracy more directly than model size. GLM-5.2's stronger performance on this metric comes despite being open-source and freely available under MIT licensing. The findings have generated discussion among developers on Hacker News, with 152 upvotes and 39 comments as of publication. The results may influence adoption decisions for organizations prioritizing accuracy over proprietary features, particularly in applications where false information carries significant risk.