Aug 14, 2026 · 5 min read

Baidu Unlimited OCR API: Pricing, Rate Limits, and Self-Hosting Guide

Baidu Unlimited OCR is the best free OCR model available in 2026. It is MIT-licensed, runs on your own hardware, and costs nothing per page. But “free” does not mean “no cost.” You still need to pay for compute, manage rate limits, and handle deployment.

Here is the complete breakdown of what Baidu Unlimited OCR actually costs and how to deploy it properly.

The cost structure

Baidu Unlimited OCR has no licensing fees. It is MIT-licensed, which means you can use it commercially, modify it, and redistribute it without paying Baidu anything.

But you still pay for:

Compute:

GPU: Recommended 8GB+ VRAM for reasonable speed
CPU: Works but much slower (10-30 seconds per page vs 1-2 seconds on GPU)
RAM: 4-8GB depending on batch size

Storage:

Model files: ~2-4GB depending on variant
Temporary files: Varies by workload

Infrastructure:

Server hosting if running in the cloud
Bandwidth for API requests
Monitoring and logging

Self-hosting costs

If you run Baidu Unlimited OCR on your own hardware:

On a consumer GPU (RTX 3060 12GB):

Speed: ~1-2 seconds per page
Cost: Electricity only (~$0.10-0.30/day depending on usage)
Throughput: ~30-60 pages/minute

On a cloud GPU (RunPod, Vast.ai):

Speed: ~0.5-1 second per page (A100)
Cost: $0.50-2.00/hour for GPU rental
Throughput: ~60-120 pages/minute

On CPU only:

Speed: ~10-30 seconds per page
Cost: Server hosting only
Throughput: ~2-6 pages/minute

For most use cases, a consumer GPU is sufficient. If you need to process thousands of pages per hour, a cloud GPU is more cost-effective than buying hardware.

Rate limits

Since Baidu Unlimited OCR runs on your own hardware, there are no API rate limits from Baidu. You control the throughput entirely.

However, you may hit rate limits from:

Your own infrastructure:

GPU memory limits batch size
Network bandwidth limits concurrent requests
Server CPU limits concurrent processing

If you use a cloud provider:

RunPod: No hard rate limits, but GPU availability varies
Vast.ai: Depends on the specific instance
AWS/GCP: Rate limits vary by instance type

Practical throughput estimates:

Hardware	Pages/Minute	Pages/Hour
RTX 3060 (12GB)	30-60	1,800-3,600
RTX 4090 (24GB)	60-120	3,600-7,200
A100 (80GB)	120-240	7,200-14,400
CPU only	2-6	120-360

API deployment

If you want to expose Baidu Unlimited OCR as an API endpoint, here is a simple FastAPI setup:

from fastapi import FastAPI, UploadFile
from paddleocr import PaddleOCR
import uvicorn

app = FastAPI()
ocr = PaddleOCR(use_angle_cls=True, lang='en')

@app.post("/ocr")
async def ocr_endpoint(file: UploadFile):
    contents = await file.read()
    result = ocr.ocr(contents)
    return {"text": result}

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)

For production use, add:

Rate limiting (e.g., 100 requests/minute per client)
Authentication (API keys or JWT)
Monitoring (Prometheus metrics)
Load balancing (multiple GPU workers)

Comparison to cloud OCR APIs

Service	Cost per 1000 pages	Speed	Setup
Baidu Unlimited OCR (self-hosted)	$0 (compute only)	1-2 sec/page	Moderate
Mistral OCR 4	$1.00	0.5-1 sec/page	Easy
Google Document AI	$1.50	1-2 sec/page	Easy
Azure AI Vision	$1.00	1-2 sec/page	Easy
AWS Textract	$1.50	2-3 sec/page	Easy

Baidu Unlimited OCR is free per page, but you pay for compute. For high-volume workloads (10,000+ pages/day), self-hosting is significantly cheaper than cloud APIs. For low-volume workloads (<1,000 pages/day), cloud APIs may be more cost-effective when you factor in setup and maintenance time.

When to use Baidu Unlimited OCR

You process 1,000+ pages per day
You need data privacy (documents never leave your infrastructure)
You want to avoid per-page costs
You have GPU infrastructure available
You need OCR in multiple languages (Baidu supports 80+ languages)

When to use cloud OCR APIs instead

You process fewer than 1,000 pages per day
You want zero setup and maintenance
You need guaranteed uptime and SLAs
You do not have GPU infrastructure
You need specialized features (form parsing, table extraction)

My take

For most developers, Baidu Unlimited OCR is the best choice if you have any GPU available. The MIT license means no per-page costs, and the quality rivals cloud APIs. The setup is straightforward if you are comfortable with Python and Docker.

If you do not have GPU infrastructure and just need occasional OCR, use Mistral OCR 4 at $1.00 per 1000 pages. The convenience is worth the cost for low-volume use cases.

For enterprise deployments where data privacy matters, Baidu Unlimited OCR is the only practical choice. Your documents never leave your infrastructure, and there are no third-party data processing agreements to worry about.

FAQ

Is Baidu Unlimited OCR really free?

Yes. The model is MIT-licensed with no per-page fees. You pay only for compute (GPU, server hosting). For self-hosted deployments, the only ongoing cost is electricity and infrastructure.

How fast is Baidu Unlimited OCR?

On a consumer GPU (RTX 3060), expect 1-2 seconds per page. On a cloud GPU (A100), expect 0.5-1 seconds per page. CPU-only deployments are much slower at 10-30 seconds per page.

What languages does Baidu Unlimited OCR support?

Baidu Unlimited OCR supports 80+ languages including English, Chinese, Japanese, Korean, and most European languages. It is particularly strong for Chinese text recognition.

Can I use Baidu Unlimited OCR commercially?

Yes. The MIT license allows commercial use, modification, and redistribution. You can deploy it in production, offer it as a service, or integrate it into commercial products without paying Baidu.

How does Baidu Unlimited OCR compare to Mistral OCR 4?

Baidu Unlimited OCR is free (self-hosted) while Mistral OCR 4 costs $1.00 per 1000 pages. Quality is comparable for most use cases. Baidu is better for high-volume and privacy-sensitive work. Mistral is better for low-volume and zero-setup use cases.