multimodal benchmark
OmniDocBench 1.5 is a comprehensive benchmark for evaluating multimodal large language models on document understanding tasks, including OCR, document parsing, information extraction, and visual question answering across diverse document types. Lower Overall Edit Distance scores are better.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | MI | 91.6% | 100.0% | 17 | C | |
| 02 | AC | 91.4% | 93.8% | 17 | C | |
| 03 | AC | 91.2% | 87.5% | 17 | C | |
| 04 | AC | 89.9% | 81.3% | 17 | C | |
| 05 | AC | 89.8% | 75.0% | 17 | C | |
| 06 | AC | 89.3% | 68.8% | 17 | C | |
| 07 | OP | 89.1% | 62.5% | 17 | C | |
| 08 | AC | 88.9% | 56.3% | 17 | C | |
| 09 | MA | 88.8% | 50.0% | 17 | C | |
| 10 | OP | 87.5% | 43.8% | 17 | C | |
| 11 | OP | 87.4% | 37.5% | 17 | C | |
| 12 | OP | 75.8% | 31.3% | 17 | C | |
| 13 | ME | 75.8% | 25.0% | 17 | C | |
| 14 | GO | 31.9% | 18.8% | 17 | C | |
| 15 | GO | 16.4% | 12.5% | 17 | C | |
| 16 | GO | 12.1% | 6.3% | 17 | C | |
| 17 | GO | 11.5% | 0.0% | 17 | C |
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
What OmniDocBench 1.5 measures and how its scores work.
OmniDocBench 1.5 is a comprehensive benchmark for evaluating multimodal large language models on document understanding tasks, including OCR, document parsing, information extraction, and visual question answering across diverse document types. Lower Overall Edit Distance scores are better.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about OmniDocBench 1.5.
MiniMax M3 is currently ranked first with 91.6%.
OmniDocBench 1.5 is a comprehensive benchmark for evaluating multimodal large language models on document understanding tasks, including OCR, document parsing, information extraction, and visual question answering across diverse document types. Lower Overall Edit Distance scores are better.
Yes. Higher values rank better for this benchmark.
17 model results are currently shown.
Yes. This benchmark can contribute to the current LLMBoard capability score.