Artificial Analysis Long Context Reasoning Benchmark Leaderboard
AA-LCR v1.1
점수
AA-LCR v1.1: 점수
AA-LCR v1.1: 점수 vs. 작업당 비용
토큰 사용량
AA-LCR v1.1: 작업당 출력 토큰
비용
AA-LCR v1.1: 작업당 비용
속도
AA-LCR v1.1: 작업당 시간
점수 vs. 출시일
AA-LCR v1.1: 점수 vs. 출시일
예시 작업
자주 묻는 질문
Artificial Analysis Long Context Reasoning은 AI 모델이 장문 문서에서 정보를 추출하고 연결하여 추론할 수 있는지 측정합니다. 다양한 분야와 형식의 문서를 사용하는 100개 문항으로 구성됩니다.
AA-LCR은 개방형 답변 문항을 통과 또는 실패로 채점합니다. 다른 LLM이 모델의 답변을 공식 답변과 동등하다고 판단하면 점수를 받습니다. 최종 AA-LCR 점수는 벤치마크 전체에서 모델의 평균 통과율입니다.
AA-LCR 결과가 공개된 모델 중 Kimi K3 (Max)의 점수가 88.7%로 가장 높습니다. 모델 보기
AA-LCR에는 기업 보고서, 업계 보고서, 정부 의견 수렴 문서, 학술 논문, 법률 문서, 마케팅 자료, 설문 보고서 등의 장문 문서 세트가 포함됩니다.
큰 컨텍스트 창이 있다고 해서 모델이 장문 문서를 효과적으로 추론할 수 있는 것은 아닙니다. AA-LCR은 긴 입력에서 정보를 찾고 연결하고 종합할 수 있는지 평가하며, 이는 재무 분석, 법률 검토, 연구, 기업 문서 업무에 중요합니다.
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