すべての評価

Harvey LAB-AA v1.1 Benchmark Leaderboard

Artificial Analysis' implementation of Harvey's Legal Agent Benchmark (LAB), testing AI agents on real-world legal work from Harvey's dataset of 120 private tasks spanning 24 legal practice areas. v1.1, built in collaboration with Harvey, checks every deliverable against the task's source documents for hallucinations, so work that passes every rubric criterion but contains a material hallucination receives no credit. A panel of three judges grades each deliverable criterion-by-criterion.
タスク例を見る

v1.1 の変更点

v1.1 は v1.0 を置き換えるもので、バージョン間でスコアは比較できません。Harvey が法律専門家と行った調査では、幻覚が弁護士がどの出力を好むかを左右する主要な要因であることがわかりました。そこで Harvey と協力し、採点に幻覚チェックを追加しました。

  • タスクと基準を改善した、Harvey の最新の非公開データセット
  • すべての成果物をタスクのソース文書と照合する新しい幻覚チェック。重大な幻覚は採点でペナルティを受けます
  • 採点者を GPT-6 Sol、Grok 4.7、Claude Opus 5.5 に更新しました。自己選好はごくわずかでしたが、偏りを抑えるため3つの結果を平均します

Harvey LAB-AA v1.1

Muse Wonder Full (Max)がHarvey LAB-AA v1.1で最高スコア13.1%を獲得。次いでMuse Wonder (Max)(スコア:10.0%)、Grok 4.7 (Xhigh)(スコア:9.4%)

スコア

Harvey LAB-AA v1.1: 幻覚ゲート適用後の全項目合格率

全評価基準に合格と判定した評価者の割合をタスクごとに平均した値。重大な幻覚があるタスクは0として扱う · Artificial Analysisによる独立ベンチマーク
No publicly available API

幻覚

Harvey LAB-AA v1.1: タスクあたりの幻覚

Upheld hallucination flags per task, split by severity · Material flags would mislead a reader on a substantive point, minor flags are real errors unlikely to affect the legal interpretation, and only material flags affect the headline score · Lower is better
No publicly available API

幻覚ゲート適用後の準合格率

Harvey LAB-AA v1.1: 幻覚ゲート適用後の準合格率

Average over tasks of the share of the judge panel that missed 0, <=1 and <=2 criteria · Tasks with at least 1 material hallucination count at 0% · Higher is better
未達の基準数で並べ替え
No publicly available API

スコア比較

Harvey LAB-AA v1.1: 幻覚ゲート適用後の全項目合格率とArtificial Analysis Intelligence Indexの比較

幻覚ゲート適用後の全項目合格率は、すべての基準に合格と判定した評価者の平均割合です。重大な幻覚があるタスクは0として扱います · Artificial Analysis Intelligence Indexは、評価スイート全体で一般的な能力を測定します · 両軸とも高いほど良好
Most attractive quadrant

コスト

Harvey LAB-AA v1.1:タスクあたりのコスト

タスクあたりの平均コスト(USD)。入力、キャッシュヒット、キャッシュ書き込み、推論、回答トークン別

トークン使用量

Harvey LAB-AA v1.1:タスクあたりの出力トークン

1タスクの実行に使用した出力トークン(推論トークンと回答トークンの内訳)
No publicly available API

速度

Harvey LAB-AA v1.1:タスクあたりの時間

Weighted average decode time (minutes) per task; excludes TTFT and overhead time · Lower is better

ターン数

Harvey LAB-AA v1.1: タスク当たり平均ターン数

Average number of model turns per Harvey LAB-AA v1.1 task · Lower is better
No publicly available API

分野別スコア

Harvey LAB-AA v1.1: 分野別幻覚ゲート適用後の全項目合格率(正規化)

Harvey LAB-AA v1.1の幻覚ゲート適用後の全項目合格率(法律分野別) · 分野あたり5タスク · 表示中のモデル間で分野ごとにスコアを正規化します。緑はその分野の最高スコア、赤は最低スコアです

モデルサイズ(オープンウェイトモデルのみ)

Harvey LAB-AA v1.1: 幻覚ゲート適用後の全項目合格率と総パラメーター数の比較

Harvey LAB-AA v1.1の幻覚ゲート適用後の全項目合格率 · パラメーター数(十億単位) · オープンウェイトモデルのみ
Most attractive quadrant
Pareto line

スコア vs. リリース日

Harvey LAB-AA v1.1: 幻覚ゲート適用後の全項目合格率とリリース日の比較

Most attractive region

タスクと提出物の例

公開タスクセットにあるHarvey LABの代表的なタスク、各モデルに渡された参照ファイル、生成された成果物を確認できます。

Mergers & Acquisitions

指示

Review the attached acquisition data room contracts and internal memo for change of control and assignment provisions, and prepare a comprehensive deal team report.

Output: coc-analysis-report.docx

成果物

モデルが作成する必要がある成果物

  • coc-analysis-report.docxA comprehensive deal team report analyzing change of control and assignment provisions across the target’s material contracts.

参照ファイル

モデルに提供

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モデルの提出物

各モデルが作成した成果物

Claude Opus 5.5 (max with fallback) - coc-analysis-report.docx
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ランキング

開発元
名前
Hallucination-Gated All-Pass Rate
Criterion Pass Rate
タスクあたりの重大な幻覚
タスクあたりのコスト
リリース日
1
Meta logoMeta
Muse Wonder Full (Max)13.1%95.5%0.62-2026年10月
2
Meta logoMeta
Muse Wonder (Max)10.0%95.1%0.89$13.862026年10月
3
SpaceXAI logoSpaceXAI
Grok 4.7 (Xhigh)9.4%92.8%0.74$9.492026年9月
4
Meta logoMeta
Muse Spark 1.3 (Max)8.9%96.0%1.68$4.212026年9月
5
OpenAI logoOpenAI
GPT-6 Astra (Max)8.6%90.6%0.03$13.672026年9月
6
OpenAI logoOpenAI
GPT-6.1 Sol (Max)6.9%90.6%0.09$2.482026年9月
7
Anthropic logoAnthropic
Claude Fable 5.1 (Max, Default Fallback)6.4%92.4%1.32$21.732026年9月
8
Kimi logoKimi
Kimi K3 (Max)5.3%93.0%2.09$6.192026年7月
9
Anthropic logoAnthropic
Claude Opus 5.5 (Max, Default Fallback)4.2%90.0%0.59$17.932026年9月
10
OpenAI logoOpenAI
GPT-6 Sol (Max)3.6%86.9%0.07$3.332026年9月
11
OpenAI logoOpenAI
GPT-6 Luna (Max)3.3%86.0%0.38$0.222026年9月
12
Mistral logoMistral
Mistral Large 4 Preview3.1%93.0%2.11$2.542026年10月
13
Anthropic logoAnthropic
Claude Sonnet 5.5 (Max, Default Fallback)2.8%92.1%1.03$14.032026年9月
14
Anthropic logoAnthropic
Claude Haiku 5.5 (Xhigh)2.8%88.0%1.61$0.432026年10月
15
DeepSeek logoDeepSeek
DeepSeek V4.1 Flash (Max)1.7%92.5%2.58$0.592026年9月

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