Executive Summary
Vision-language models have crossed the production readiness threshold for document understanding applications, while industrial inspection and accessibility use cases require additional validation. GPT-5V and Gemini 2.5 Vision lead on accuracy; Claude 4 Vision leads on instruction following.
Benchmark Results
Document Understanding
| Model | Table Extraction | Handwriting | Multi-page Context |
|---|---|---|---|
| GPT-5V | 94.2% | 89.7% | 92.1% |
| Gemini 2.5 Vision | 93.8% | 91.2% | 90.4% |
| Claude 4 Vision | 91.5% | 87.3% | 93.8% |
| Qwen2-VL Max | 88.4% | 82.1% | 85.6% |
Industrial Inspection (Defect Detection)
| Model | Precision | Recall | F1 Score |
|---|---|---|---|
| GPT-5V | 0.89 | 0.84 | 0.86 |
| Gemini 2.5 Vision | 0.87 | 0.86 | 0.86 |
| Claude 4 Vision | 0.85 | 0.82 | 0.83 |
| LLaVA-NeXT | 0.78 | 0.74 | 0.76 |
Production Readiness Assessment
Ready for deployment: Document understanding, OCR replacement, accessibility alt-text generation Pilot stage: Industrial quality inspection, medical image pre-screening Research only: Autonomous navigation, real-time safety monitoring
Full methodology: methodology