Compare the best free OCR APIs and tools: OCR.space, Google Cloud Vision, Tesseract, Eden AI, EasyOCR. Python code examples and accuracy comparison.
Optical Character Recognition (OCR) converts images, scanned documents, and PDFs into machine-readable text. In 2026, developers have access to several powerful OCR APIs and libraries — many with generous free tiers. This guide reviews the five best free OCR tools for text extraction, with code examples, accuracy comparisons, and guidance on choosing the right solution for your project.
OCR (Optical Character Recognition) is the technology that recognizes text within images, photographs, scanned documents, and PDF files. An OCR API lets you send an image or document and receive structured text output via a REST endpoint, without running complex ML models on your own infrastructure.
Common OCR use cases include:
| Tool | Type | Free Tier | Languages | Handwriting? | Best For |
|---|---|---|---|---|---|
| OCR.space | Cloud API | 25,000 requests/month | 25+ | Limited | Simple integration, generous limits |
| Google Cloud Vision | Cloud API | 1,000 units/month | 100+ | Yes | Highest accuracy, handwriting support |
| Tesseract | Self-hosted | Unlimited (open source) | 100+ | Limited | Full control, offline, no API costs |
| Eden AI | API aggregator | $1 free credit | Varies by engine | Via Google/Azure engines | Compare multiple OCR engines |
| EasyOCR | Python library | Unlimited (open source) | 80+ | Limited | Quick local setup, GPU-accelerated |
OCR.space provides one of the most generous free OCR APIs available. With 25,000 free requests per month and no credit card required, it is an excellent choice for most developer projects.
Google Cloud Vision offers industry-leading OCR accuracy, powered by the same technology behind Google Lens and Google Photos text search. The free tier includes 1,000 units per month.
Tesseract is Google's open-source OCR engine, now maintained by the community. It runs locally on your machine, costs nothing, and supports 100+ languages. Version 5.x (2026) includes LSTM-based neural network recognition.
pytesseract for easy integrationEden AI is a unified API that lets you access multiple OCR providers — Google, Microsoft Azure, Amazon Textract, and others — through a single endpoint. This lets you compare accuracy and cost across providers.
EasyOCR is a Python library that provides OCR capability without any cloud dependency. It supports 80+ languages, runs on CPU or GPU, and delivers good accuracy out of the box with minimal configuration.
The following example demonstrates how to extract text from an image using the OCR.space free API:
import requests
# OCR.space free API - get your key at https://ocr.space/ocrapi
API_KEY = "your-ocr-space-api-key"
def extract_text_from_image(image_path):
"""Extract text from a local image file using OCR.space API."""
url = "https://api.ocr.space/parse/image"
with open(image_path, "rb") as f:
response = requests.post(
url,
files={"file": f},
data={
"apikey": API_KEY,
"language": "eng", # English (use "spa", "deu", etc.)
"isOverlayRequired": True, # Include word bounding boxes
"OCREngine": 2, # Engine 2 for better accuracy
"isTable": True, # Enable table recognition
"scale": True # Auto-upscale small images
}
)
result = response.json()
if result["IsErroredOnProcessing"]:
print(f"Error: {result['ErrorMessage']}")
return None
# Extract text from all pages
full_text = ""
for page in result["ParsedResults"]:
full_text += page["ParsedText"]
return full_text
def extract_text_from_url(image_url):
"""Extract text from an image URL using OCR.space API."""
url = "https://api.ocr.space/parse/imageurl"
response = requests.get(url, params={
"apikey": API_KEY,
"url": image_url,
"language": "eng",
"OCREngine": 2
})
result = response.json()
return result["ParsedResults"][0]["ParsedText"]
# Usage examples
if __name__ == "__main__":
# From a local file
text = extract_text_from_image("receipt.jpg")
print("Extracted text:")
print(text)
# From a URL
url_text = extract_text_from_url("https://example.com/invoice.png")
print("\nText from URL:")
print(url_text)
Tip: For processing PDF documents, combine OCR with our PDF Toolkit API. Use the PDF API to split multi-page documents into individual pages, then run OCR on each page for full text extraction.
Extract vendor names, dates, line items, and totals from invoices and receipts. Combine OCR output with an LLM (see our free LLM API guide) to parse unstructured OCR text into structured JSON for accounting systems.
Build automated pipelines that scan paper documents, extract text via OCR, and index them for full-text search. Use our PDF API to merge extracted pages back into searchable PDF files.
Replace manual form entry by photographing physical forms and extracting field values with OCR. Works well for healthcare forms, government applications, and logistics paperwork.
Make image-heavy websites accessible to screen readers by extracting text from images and infographics. This improves both accessibility compliance and SEO (search engines can index the extracted text).
For complete document processing workflows, explore our API hub at DevProToolkit, which includes PDF manipulation, AI text processing, image generation, and 100+ other developer tools — all accessible through a single API key.
Combine OCR with our PDF API for merging, splitting, and compressing documents. Plus AI text tools for summarization and translation. One API key for everything.
Sign Up Free →OCR.space is the best free OCR API for most developers, offering 25,000 free requests per month with no credit card. For the highest accuracy, Google Cloud Vision offers 1,000 free units per month but requires a billing account.
Yes, but accuracy varies. Google Cloud Vision has the best handwriting recognition. Tesseract and EasyOCR have limited handwriting support. OCR.space works best with printed text. For critical handwriting recognition, Google Cloud Vision is the recommended choice.
Most OCR APIs support PNG, JPG, GIF, BMP, and TIFF. OCR.space and Google Cloud Vision also accept PDF files directly. For best results, use high-resolution images (300+ DPI) with good contrast.
On clean, printed text with good image quality, free OCR tools achieve 95-99% accuracy. Accuracy drops with low resolution, poor lighting, handwriting, unusual fonts, or complex layouts. Google Cloud Vision typically achieves the highest accuracy, followed by OCR.space Engine 2.
Yes. OCR.space and Google Cloud Vision accept PDF input directly. For Tesseract and EasyOCR, convert PDF pages to images first (using a tool like our PDF API), then run OCR on each image. Our PDF Toolkit API can extract text from digital PDFs without OCR, and split scanned PDFs into images for OCR processing.
Yes. Tesseract 5.x with LSTM models provides competitive accuracy for printed text. It is the best choice when you need full privacy, offline capability, or want to avoid recurring API costs. For the highest accuracy on diverse inputs, cloud APIs are still superior.
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