Data Notice: AI model performance data and benchmark scores referenced in this medical ai accuracy leaderboard article reflect evaluations as of early 2026. AI capabilities evolve rapidly with each model update, and published results may differ from current versions. [medical-ai-accuracy-leaderboard]

Medical AI Accuracy Leaderboard

DISCLAIMER: The content in this medical ai accuracy leaderboard article is informational and educational only and does not constitute medical advice, diagnosis, or treatment. Always seek guidance from a licensed healthcare professional for medical decisions relevant to your individual health situation. [medical-ai-accuracy-leaderboard]

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How do the leading AI models stack up on medical accuracy? This leaderboard aggregates performance across published benchmarks and our own evaluation framework, updated regularly as new data becomes available.

Overall Medical AI Leaderboard (March 2026)

Rank	Model	MedQA Score	Safety Score	mdtalks Composite	Availability
1	AMIE (Google)	~92%	8/10	9.0/10	Research only
2	Med-PaLM 2 (Google)	~86.5%	8/10	8.5/10	Restricted API
3	Claude 4 (Anthropic)	~84%	10/10	8.4/10	Public
4	GPT-4 (OpenAI)	~86%	7/10	8.2/10	Public
5	Claude 3.5 (Anthropic)	~82%	10/10	8.1/10	Public
6	Gemini Ultra (Google)	~84%	7/10	7.8/10	Public
7	GPT-4o (OpenAI)	~84%	7/10	7.7/10	Public
8	Gemini Pro (Google)	~78%	7/10	7.2/10	Public
9	Meditron 70B (EPFL)	~62%	5/10	6.0/10	Open source
10	MedAlpaca 13B	~52%	4/10	5.2/10	Open source

How We Calculate the Composite Score

Our composite score weights multiple dimensions:

• Factual Accuracy (30%) — Benchmark performance + our evaluation
• Safety (25%) — Caveats, disclaimers, urgency communication, crisis resources
• Completeness (20%) — Coverage of differential diagnoses, treatment options, red flags
• Clarity (10%) — Patient accessibility of language
• Source Quality (10%) — Verifiable citations and guideline references
• Appropriate Hedging (5%) — Uncertainty communication

Medical AI Accuracy: How We Benchmark Health AI Responses

Leaderboard by Category

Best for Patient Safety

1. Claude 4 — 10/10
2. Claude 3.5 — 10/10
3. Med-PaLM 2 — 8/10
4. GPT-4 — 7/10

Best for Clinical Knowledge

1. AMIE — 92% MedQA
2. Med-PaLM 2 — 86.5% MedQA
3. GPT-4 — ~86% MedQA
4. Claude 4 — ~84% MedQA

Best for Patient Communication

1. Claude 3.5 / Claude 4
2. GPT-4
3. Gemini
4. Med-PaLM 2

Best Publicly Available Model

1. Claude 4 (Composite: 8.4/10)
2. GPT-4 (Composite: 8.2/10)
3. Gemini Ultra (Composite: 7.8/10)

Performance by Medical Specialty

Specialty	Best Model	Score	Runner-Up
Cardiology	Med-PaLM 2	8.6/10	Claude 3.5
Dermatology	Claude 3.5	8.0/10	Med-PaLM 2
Mental Health	Claude 3.5	8.8/10	GPT-4
Pediatrics	Claude 3.5	9.0/10	Med-PaLM 2
Orthopedics	Med-PaLM 2	8.0/10	Claude 3.5
Endocrinology	Med-PaLM 2	8.5/10	GPT-4
Gastroenterology	Claude 3.5	8.7/10	Med-PaLM 2
OB/GYN	Claude 3.5	9.3/10	Med-PaLM 2

Important Caveats

1. Benchmark scores are not clinical competence. MedQA scores measure performance on multiple-choice medical questions, not real-world clinical capability.
2. Safety scores are our editorial assessment. They reflect how well models communicate limitations and recommend professional care, not an absolute measure of safety.
3. Models are continuously updated. Scores may change as models receive updates.
4. Our evaluations have limitations. Sample sizes, evaluator expertise, and topic selection all influence scores.
5. Availability matters. A model with a perfect score that nobody can use has limited real-world value.

How This Leaderboard Differs From Others

Most AI leaderboards focus on raw benchmark performance. Our leaderboard uniquely weights:

• Safety as 25% of the score — reflecting the reality that a highly accurate but unsafe medical AI is worse than a moderately accurate but safe one
• Patient accessibility — because most medical AI users are patients, not clinicians
• Real-world availability — because access determines impact

Key Takeaways

• AMIE leads on raw medical benchmarks but is not publicly available. Among accessible models, Claude 4 leads our composite ranking due to exceptional safety communication.
• Safety and accuracy are both critical — a model that is 95% accurate but omits important safety caveats may be more dangerous than one that is 85% accurate with excellent safety communication.
• No single model dominates across all specialties. Performance varies by medical domain.
• This leaderboard is a guide, not a definitive ranking. Always evaluate AI for your specific use case.

Next Steps

• Understand our methodology: Medical AI Accuracy: How We Benchmark Health AI Responses
• Try comparing models yourself: Medical AI Comparison Tool: Ask Any Health Question
• Read model profiles: Guide to Medical AI Models: AMIE, Med-PaLM, GPT-4, and More
• See models in action: AI Answers About Headaches: Model Comparison

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Published on mdtalks.com | Editorial Team | Last updated: 2026-03-10

DISCLAIMER: The content in this medical ai accuracy leaderboard article is informational and educational only and does not constitute medical advice, diagnosis, or treatment. Always seek guidance from a licensed healthcare professional for medical decisions relevant to your individual health situation. [medical-ai-accuracy-leaderboard]

Sources

1. NIH: AI-Driven Clinical Decision Support — accessed March 25, 2026
2. FDA: AI/ML-Based Software as a Medical Device — accessed March 25, 2026