Artificial Analysis Long Context Reasoning Benchmark Leaderboard
AA-LCR v1.1
スコア
AA-LCR v1.1：スコア
AA-LCR v1.1：スコア vs. タスクあたりのコスト
トークン使用量
AA-LCR v1.1：タスクあたりの出力トークン
コスト
AA-LCR v1.1：タスクあたりのコスト
速度
AA-LCR v1.1：タスクあたりの時間
スコア vs. リリース日
AA-LCR v1.1：スコア vs. リリース日
タスク例
よくある質問
Artificial Analysis Long Context Reasoning は、AI モデルが長い文書から情報を抽出し、関連付けて推論できるかを測定します。さまざまな分野と形式の文書を使った 100 問で構成されます。
AA-LCR は自由回答問題を合格または不合格で採点します。別の LLM がモデルの回答を公式回答と同等と判定すると得点になります。最終的な AA-LCR スコアは、ベンチマーク全体におけるモデルの平均合格率です。
AA-LCR の公開結果があるモデルの中で、Kimi K3 (Max) が 88.7% で最高スコアです。 モデルを見る
AA-LCR には、企業レポート、業界レポート、政府の意見募集文書、学術論文、法的文書、マーケティング資料、調査レポートなどの長文書セットが含まれます。
大きなコンテキストウィンドウがあっても、長い文書を効果的に推論できるとは限りません。AA-LCR は、長い入力から情報を見つけ、関連付け、統合できるかを評価します。これは財務分析、法務レビュー、研究、企業文書の処理などで重要です。
評価を探す
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