Table of Contents
Quick Verdict
PaddleOCR processes 104.7 requests per second at a 9 ms median latency. Read that again: nine milliseconds. That is faster than most network round trips. For a document OCR API on a dedicated GPU server, PaddleOCR’s throughput is 2.2x higher than YOLOv8’s 47.8 req/s, and its latency is less than half. On raw API serving metrics, PaddleOCR is in a different league.
YOLOv8 provides superior layout detection for complex documents, but for a text extraction API endpoint, PaddleOCR is the unambiguous winner.
Full data below. More at the GPU comparisons hub.
Specs Comparison
PaddleOCR’s 12M parameters versus YOLOv8’s 44M explains the throughput gap. Lighter models serve faster, and PaddleOCR is purpose-built for text recognition rather than general object detection.
| Specification | YOLOv8 | PaddleOCR |
|---|---|---|
| Parameters | ~44M (YOLOv8x) | ~12M (PP-OCRv4) |
| Architecture | CSPDarknet + PAN | DB + SVTR |
| Context Length | 640×640 | Variable |
| VRAM (FP16) | 1.5 GB | 0.8 GB |
| VRAM (INT4) | N/A | N/A |
| Licence | AGPL-3.0 | Apache 2.0 |
Note: YOLOv8’s AGPL-3.0 licence requires open-sourcing derivative works, which may be a constraint for commercial API services. PaddleOCR’s Apache 2.0 is more permissive. Guides: YOLOv8 VRAM requirements and PaddleOCR VRAM requirements.
API Throughput Benchmark
Tested on an NVIDIA RTX 3090 under sustained concurrent load. See our benchmark tool.
| Model (INT4) | Requests/sec | p50 Latency (ms) | p99 Latency (ms) | VRAM Used |
|---|---|---|---|---|
| YOLOv8 | 47.8 | 24 | 47 | 1.5 GB |
| PaddleOCR | 104.7 | 9 | 39 | 0.8 GB |
PaddleOCR’s p99 latency (39 ms) is lower than YOLOv8’s p50 (24 ms) — a stunning consistency advantage. For SLA-bound APIs, PaddleOCR provides maximum predictability. See our best GPU for LLM inference guide.
See also: YOLOv8 vs PaddleOCR for Document Processing / RAG for a related comparison.
See also: SD 1.5 vs SDXL for API Serving (Throughput) for a related comparison.
Cost Analysis
PaddleOCR processes roughly 2x more pages per pound of compute cost. At these volumes, self-hosting is dramatically cheaper than any cloud OCR service.
| Cost Factor | YOLOv8 | PaddleOCR |
|---|---|---|
| GPU Required | RTX 3090 (24 GB) | RTX 3090 (24 GB) |
| VRAM Used | 1.5 GB | 0.8 GB |
| Pages/min | 500 | 596 |
| Cost/10K Pages | £0.05 | £0.024 |
See our cost calculator.
Recommendation
Choose PaddleOCR for text extraction APIs. Its 2.2x higher throughput, sub-10ms median latency, lower VRAM footprint, and Apache 2.0 licence make it the clear choice for any document OCR endpoint.
Choose YOLOv8 for layout analysis APIs where the endpoint needs to identify document regions (tables, figures, headers) rather than extract text. Note the AGPL-3.0 licence implications for commercial services.
Serve on dedicated GPU servers for consistent OCR API performance.
Deploy the Winner
Run YOLOv8 or PaddleOCR on bare-metal GPU servers with full root access, no shared resources, and no token limits.
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