Patients increasingly turn to large language models (LLMs) for medical self-diagnosis in both English and non-English, often in colloquial language. We evaluate LLM diagnostic performance on rheumatological skin conditions across lay descriptions in English, Spanish, Hindi, and Mandarin, collected from native speakers without medical training, and clinical descriptions in English. Lay descriptions substantially reduce diagnostic accuracy relative to clinical ones, and the gap widens further across non-English languages. A diagnostic-focused system prompt narrows the lay-vs-clinical gap but does little to close the cross-language gap. Current LLMs appear to reproduce, and in some settings amplify, communication-driven disparities documented in clinical medicine.