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Medical Long Context Reasoning (MLCR-AA, October 2026 methodology)

Professional Work

Artificial Analysis' revised MLCR-AA methodology, first published between October 19 and 21, 2026: 60 private held-out expert-tier and compound questions from Wisedocs Medical Long Context Reasoning, over synthetic records of about 25,000 to 64,000 tokens, each run three times. A response passes when a majority of three judges (Claude Opus 5.5, GPT-6.1 Sol and Grok 4.7 at medium effort) each find it complete, naming every documentation gap on the way to the ground-truth conclusion, and free of claims that contradict the record. Empty responses fail. The earlier conciseness gate is gone and AA re-scored every model, so these results are not comparable with mlcr-aa.

Top models (higher is better)

ModelScore
Claude Sonnet 5.541.7
GPT-6 Astra41.7
GPT-6.1 Sol38.3
Claude Haiku 5.535.0
GPT-6 Sol33.9
GPT-5.5 Instant (2026-06-25 hosted snapshot)31.7
Qwen3.8 2.4T A95B30.6
GPT-5.6 Sol30.0
GPT-5.528.9
Claude Opus 5.527.8
GPT-5.6 Terra27.2
GPT-6 Luna26.1
Qwen3.8-Max26.1
DeepSeek V4.1 Flash23.9
Qwen3.8 27B22.8
Kimi K321.7
Grok 4.721.1
Claude Fable 520.6
Qwen3.8-Flash-Next20.6
GPT-5.4 Mini20.0
GPT-5.6 Luna20.0
Qwen3.8 Max (0902)20.0
Opus 4.819.4
Claude Fable 5.118.3
Grok 4.618.3
Step 5 Preview18.3
GLM-5.317.2
GPT-5.4 Nano16.1
Grok 4.516.1
Gemini 3.8 Flash15.6
Muse Spark 1.315.6
Qwen3.7-Max (source unspecified)14.4
Claude Opus 513.9
Gemini 4 Argon13.9
GLM-5.212.8
MiMo-V2.6-Pro12.8
Gemini 2.5 Pro12.2
Gemini 3.7 Flash12.2
Kimi K2.7 Code12.2
Ling 3.1 Flash12.2
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