Best LLMs for wide web research

WANDR

Tests collecting and organizing facts across a broad research assignment, helping you assess AI support for client research that involves many separate lookups. This offline-search soft-F1 evaluation differs from live-web runs and is not a project-completion percentage.

Updated: Nov 9, 2026Data as of: Nov 9, 2026

Limited reportingNot saturated

Official benchmark

WANDR results. Each row identifies its benchmark version and evaluation track. Scores from different versions are not directly comparable. Best effort from the latest stored report date per model and version.
Model / creator	Version	Reported score
Claude Fable 5.2Anthropic · Proprietary	Anthropic offline / relaxed soft F1	82.1%
Claude Opus 5.5Anthropic · Proprietary	Anthropic offline / relaxed soft F1	72.3%
Claude Fable 5.1Anthropic · Proprietary	Anthropic offline / relaxed soft F1	68.7%

View all 3 published reports

Claude Fable 5.282.1%

Anthropic offline / relaxed soft F1

effort: max · 500 tasks; modified soft F1; frozen web index; Opus 4.6 grader; 980K budget. Not directly comparable with Perplexity live-web runs. · Tools enabled

Anthropic ↗

Claude Opus 5.572.3%

Anthropic offline / relaxed soft F1

effort: highest available · November 9 launch-table comparison; highest available effort unless explicitly noted. Preserve the benchmark track and model configuration; competitor figures are as reported by Anthropic. · Tools enabled

Anthropic ↗

Claude Fable 5.168.7%

Anthropic offline / relaxed soft F1

Anthropic ↗

Sources and original reports ↗

Other benchmarks

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Harvey LAB-AA

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