I Ran the Same Invoice Through PaddleOCR and GPT-4o

Most OCR comparisons online are SEO-optimized lists without actual test results. I wanted real numbers.

So I generated an invoice, ran it through PaddleOCR and GPT-4o, and recorded everything.

The Test

Simple invoice, white background, standard fonts. The easy case. Real documents are messier.

PaddleOCR: 4.69 seconds, 99.6% confidence

Got everything right. Every number, every dollar sign. But the output is flat - each text region becomes a separate line.

GPT-4o: 5.18 seconds, ~$0.015

GPT-4o understood this was a table and preserved the structure. The table headers align with values. If you asked "what's the total?", you could find it.

The Difference

Both took ~5 seconds. Both got the text right. But they're solving different problems:

PaddleOCR is a text extraction engine. It finds text and tells you what it says. Free, fast, accurate. That's it.

GPT-4o is a document understanding system. It reads and interprets. Costs money but thinks for you.

The Code

PaddleOCR

# pip install paddlepaddle paddleocr
from paddleocr import PaddleOCR

ocr = PaddleOCR(lang='en')
result = ocr.predict('invoice.png')

for item in result:
    for text in item.get('rec_texts', []):
        print(text)

GPT-4o

# pip install openai
import base64
from openai import OpenAI

client = OpenAI()

with open('invoice.png', 'rb') as f:
    img = base64.b64encode(f.read()).decode()

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": [
        {"type": "text", "text": "Extract all text from this image."},
        {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{img}"}}
    ]}]
)

print(response.choices[0].message.content)

My Take

Start with PaddleOCR. Free, works, handles 90% of cases. When you hit a wall - complex layouts, handwriting, documents needing interpretation - try GPT-4o on those specific cases.

More

• 47 OCR benchmarks compared
• Best OCR for invoices
• PaddleOCR vs Tesseract