Claude Opus 5.5 leads image understanding benchmarks

Claude Opus 5.5 leads LLM Stats’ image understanding rankings as of November 2026 with a score of 42.2, followed by Claude Fable 5.1 at 41.9 and GPT-6 Astra at 41.3. The evaluation covers 241 models and draws on 182 benchmarks, including MMMU for university-level visual reasoning, MathVista for chart and diagram reasoning, and OCRBench for text extraction.

Leading models go beyond object recognition to interpret charts, read handwriting, understand spatial relationships and answer questions requiring multi-step visual reasoning. Top models achieve above 90% accuracy on standard OCR benchmarks, though handwriting, low-quality scans and non-Latin scripts remain harder than clean printed text. Chart analysis works well for bar charts, line graphs and tables, but performance drops on complex multi-panel figures and unusual visualizations.

Current leading multimodal models also match text-only models on text benchmarks. Practical selection still requires testing against actual documents and tasks rather than relying solely on aggregate scores. Medical image analysis varies widely in quality, and AI should not be used for clinical diagnosis without professional supervision.