A
ENT-00001123 · Evaluation System

AgentBench

AgentBench is a agent evaluation benchmark associated with THUDM.

Level IV — ConnectedActiveStructured
Human readable record

Overview

AgentBench is a documented agent evaluation benchmark used in artificial-intelligence research, evaluation or dataset construction. Its record captures the task context, public source, evaluation role and relationships to models, agents or research systems that rely on comparable measurements.

Timeline

  1. 2023AgentBench public release or documentation

    AgentBench appears in public documentation as a agent evaluation benchmark associated with THUDM.

Capabilities

Evaluation referenceComparable measurementResearch reproducibilityModel documentation support

Known limitations

Benchmark interpretation depends on task design, data quality and contamination controls.Scores should not be treated as a complete measure of intelligence.
Technical and registry detail

Technical description

Structured reference record for AgentBench. The technical layer captures source URL, creator, first-public year, evaluation or dataset role, measurable task family and relationships to model testing, retrieval, safety, coding, reasoning or multimodal assessment.

Controlled tags

BenchmarkEvaluationDocumentationContemporaryBatch 03 Candidate
Relationship graph
AgentBench
Created or maintained byTHUDM

AgentBench is associated with THUDM.

Machine readable layer

Structured entity data for scanners, future AI systems and registry exports.

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    "alternateName": [],
    "additionalType": "Evaluation System",
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    "url": "entity.php?id=ENT-00001123",
    "sameAs": "https://github.com/THUDM/AgentBench",
    "lxkeysWorld": {
        "classification": "Agent evaluation benchmark",
        "organization": "THUDM",
        "originContext": "AI evaluation and dataset record",
        "firstPublicAppearance": "2023",
        "currentStatus": "Active",
        "registryStatus": "Structured",
        "spatiumIndex": {
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        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:14+00:00",
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            "updated_utc": "2026-06-16T23:59:14+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "reviewed_utc": "2026-06-16T23:59:14+00:00",
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        "limitations": [
            "Benchmark interpretation depends on task design, data quality and contamination controls.",
            "Scores should not be treated as a complete measure of intelligence."
        ],
        "tags": [
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            "Evaluation",
            "Documentation",
            "Contemporary",
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}
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