Best LLMs for document parsing

OmniDocBench

Tests extracting text, tables and formulas from documents, helping you choose a model for turning client files into usable data with less manual copying. These results use the reported version 1.5 evaluation.

Updated: Nov 9, 2026Data as of: Nov 8, 2026

Limited reportingSaturated

Official benchmark

OmniDocBench 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
Ling-3.2-flashAnt Ling · Proprietary	1.5 / Ant Ling launch	92.21%

View all 1 published reports

Ling-3.2-flash92.21%

1.5 / Ant Ling launch

Publisher launch/model-card report. Unspecified tool settings, effort and budgets remain unknown; not substituted for a pinned independent evaluation.

Ant Ling ↗

Sources and original reports ↗

Other benchmarks

WANDR

Tests collecting and organizing facts across a broad research assignment, helping you assess AI support for client research that involves many separate lookups.

ExploitGym

Tests finding and exploiting vulnerabilities in controlled software environments, helping authorized security teams assess AI support for testing and remediation work.

RemoteExploitBench

Tests exploit development against known vulnerabilities in controlled, remotely deployed apps, helping authorized security teams assess how AI could support validation of security findings.