GraphCanon updated Aug 14, 2026 · GitHub synced Aug 14, 2026
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Decision brief
TurboOCR, optimized for GPUs, delivers high-speed OCR with support for TensorRT FP16 acceleration and PP-OCRv5 model.
Good fit when
- When you need fast text detection and recognition on GPU-enabled systems
- For document parsing tasks where speed is critical and NVIDIA GPUs are available
Avoid when
- If your infrastructure lacks a supported NVIDIA GPU or has less than required VRAM
- In scenarios where the initial TensorRT engine build time cannot be accommodated
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of Aug 14, 2026
- Provenance
- Not a fork · Organization account
- As of Aug 14, 2026
- Security (OSV)
- No lockfile
- As of Jul 15, 2026
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Install
git clone https://github.com/aiptimizer/TurboOCRHow it fits your stack(1)
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Evidence and technical details
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Overview
TurboOCR is an OCR server optimized for fast text detection and recognition on GPU using PP-OCRv5 with TensorRT FP16 acceleration.
Capability facts
- Languages
- c++
Source: github.language · Aug 14, 2026
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README
Quick Start Requirements: Linux, NVIDIA driver 595+, Turing or newer GPU (RTX 20 series / GTX 16 series+). Plan for 4 GB VRAM text only and 8 GB for the full pipeline (layout + tables + formulas); each extra replica adds roughly another full set, so lower it on smaller cards. Fir...
For agents
This page has a .md twin and JSON over the API.