Benchmarks › MLCR-AA

MLCR-AA

Reason across long fragmented medical records
75top score · Claude Sonnet 5.5
64models ranked
24open-weights models
Pass@1 pass rate (complete and accurate)higher is better
Oct 20, 2026last updated

How the test works

1

Task

60 tasks

  • What the model doesReason across long fragmented medical records
  • Kinds of tasksMedical record reasoning
  • In → outText → Answer
2

Run

3 runs per task

  • Agent / harnessAnswer each part in one paragraph and cite record evidence unless the question specifies another format.
  • Token budgetNon-reasoning: up to 16,384 output tokens, adjusted to model limits; reasoning: model-specific maximum
  • Temperature0 for non-reasoning; 0.6 for reasoning, unless the model lab recommends otherwise
3

Score

Pass@1 (solved on the first try) pass rate (complete and accurate)

  • Graded byThree-judge majority: Claude Opus 5.5, GPT-6.1 Sol and Grok 4.7 (medium)
  • Better isHigher
  • Test setPrivate held-out expert/compound set, separate from public Wisedocs MLCR dataset

MLCR-AA leaderboardtop 10 of 64

Full leaderboard with filters →
ModelMLCR-AAPer taskPriceSpeedSupportsContext
75max
$5.46$2 / $101371M
71.1max
$7.63$10 / $50691M
66.7max
$5.98$4 / $20961M
64.4max
$8.75$10 / $50671M
63.3max
$0.21$0.10 / $0.502341M
Claude Opus 5Anthropic
59.4high
$3.61$5 / $25511M
55max
$5.09$2 / $10801M
51.1max
$0.28$0.15 / $0.501791M
GLM 5.3Z.aiOpen
48.3max
$2.01$1.40 / $4.401861M
45.6max
$4.08$5 / $25661M

MLCR-AA questions

What is MLCR-AA?›

Reason across long fragmented medical records. It has 60 tasks. Created by Wisedocs (MLCR); Artificial Analysis (AA evaluation).

Which model is best on MLCR-AA?›

Claude Sonnet 5.5 leads MLCR-AA with 75, ahead of Claude Fable 5.1 (71.1) and Claude Opus 5.5 (66.7).

What is the best open-weights model on MLCR-AA?›

GLM 5.3 Flash with 51.1, then GLM 5.3 (48.3).

How is MLCR-AA scored?›

Pass@1 (solved on the first try) pass rate (complete and accurate); three-judge majority: claude opus 5.5, gpt-6.1 sol and grok 4.7 (medium); compare expert ground truth and medical record, including contradictions and documentation gaps.; 3 runs per task per task.