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On October 22, 2026, Artificial Analysis compared the medical long-text performance of 14 models on two evaluations, MLCR-AA and HealthBench Professional. The results show that Claude Sonnet 5.5, Opus 5.5, and Fable 5.1 swept the top three spots for MLCR-AA completeness, leading the best OpenAI model by about 19 to 23 points; Opus and Sonnet scored 71.4% and 70.8% respectively on HealthBench Professional raw scores, slightly above GPT-6 Astra's 69.7%. OpenAI models, meanwhile, took the top spots for MLCR-AA accuracy; Anthropic models' single responses were about 4 to 6 times as long as OpenAI's, with accuracy of 19% to 61%, versus 89% to 97% for OpenAI. GPT-6 Astra (max) tied with Claude Sonnet 5.5 for first place on MLCR-AA and held a slight lead on the HealthBench Professional length-adjusted score; Claude Opus 5.5, however, fell from first on raw score to sixth on the length-adjusted score.
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Artificial Analysis compares medical long-text evaluation results of 14 models
Source:Artificial Analysis
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Oct 22
Artificial Analysis
Anthropic's medical answers are more comprehensive, OpenAI's are more accurate and concise
Artificial Analysis compared 14 models on MLCR-AA and HealthBench Professional: Claude Sonnet 5.5, Opus 5.5, and Fable 5.1 swept the top three spots for MLCR-AA completeness, leading the best OpenAI model by about 19-23 points; Opus and Sonnet scored 71.4% and 70.8% raw on HealthBench Professional, slightly above GPT-6 Astra's 69.7%. OpenAI models, meanwhile, took the top spots for MLCR-AA accuracy; Anthropic models' single responses were about 4-6 times longer than OpenAI's, with accuracy of only 19-61%, versus 89-97% for OpenAI. GPT-6 Astra (max) tied Claude Sonnet 5.5 for first place on MLCR-AA and held a slight lead on the HealthBench Professional length-adjusted score; Claude Opus 5.5, however, fell from first in raw score to sixth in length-adjusted score.