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MLCR-AA Accuracy (October 2026 methodology)

Professional Work

Accuracy under Artificial Analysis' October 2026 MLCR-AA methodology: the share of responses that a majority of the three judges find free of any claim contradicting the source medical record, including claims outside the ground truth, averaged over three runs of 60 questions. It is a second reading of the run behind the MLCR-AA pass rate and stays diagnostic.

Top models (higher is better)

ModelScore
GPT-6.1 Terra98.3
GPT-6.1 Sol96.7
GPT-6 Astra95.6
GPT-6 Sol95.0
Kimi K3.1 Pro93.9
GPT-6 Luna88.9
GPT-5.587.8
GPT-5.5 Instant (2026-06-25 hosted snapshot)81.1
GPT-5.6 Terra78.3
GPT-5.6 Sol76.7
Qwen3.8 2.4T A95B76.1
Qwen3.8-Max75.6
DeepSeek V4.1 Flash 101767.8
Qwen3.8 Max (0902)67.8
Grok 4.767.2
Muse Wonder65.6
GPT-5.4 Nano65.0
Beam 1.0 501B A23B64.4
GPT-5.4 Mini64.4
GPT-5.6 Luna63.9
DeepSeek V4.1 Flash61.1
Claude Sonnet 5.560.9
Claude Haiku 5.558.9
Muse Spark 1.358.9
Muse Wonder Full58.9
Qwen3.8 27B57.8
Grok 4.655.6
Qwen3.8-Flash-Next54.4
Step 5 Preview49.4
Grok 4.547.2
K2 Horizon 375B A23B47.2
Gemini 2.5 Pro46.7
MiniMax M3.1 Flash46.7
Kimi K339.4
Opus 4.837.8
Gemini 3.1 Pro Preview37.8
Ling 3.1 Flash 101937.8
Ling 3.1 Flash37.8
Claude Opus 5.537.2
Muse Spark 1.136.7
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