DeepSeek-OCR — 3 Technical Articles

Jan 30, 2026 · Artificial Intelligence

PaddleOCR‑VL‑1.5: 0.9B Model Beats Billion‑Parameter OCR Models with 94.5% Accuracy

PaddleOCR‑VL‑1.5, the latest Baidu release, uses only 0.9 B parameters to achieve 94.5% accuracy on OmniDocBench v1.5, surpassing larger open‑source and commercial OCR models, while offering multi‑task, multi‑language support, lightweight deployment, and detailed performance benchmarks.

DeepSeek-OCRGPU inferenceOCR

0 likes · 9 min read

PaddleOCR‑VL‑1.5: 0.9B Model Beats Billion‑Parameter OCR Models with 94.5% Accuracy

HyperAI Super Neural

Nov 11, 2025 · Artificial Intelligence

How Deepseek-OCR Achieves SOTA Using Ultra‑Low Visual Token Counts

Deepseek-OCR leverages a visual‑compression approach, combining DeepEncoder and the DeepSeek3B‑MoE‑A570M decoder, to represent document text with far fewer visual tokens, achieving up to 97% OCR accuracy and surpassing GOT‑OCR2.0 and MinerU2.0 on OmniDocBench, while the article offers a one‑click deployment tutorial.

DeepEncoderDeepSeek-OCRLLM

0 likes · 6 min read

How Deepseek-OCR Achieves SOTA Using Ultra‑Low Visual Token Counts

Fun with Large Models

Oct 26, 2025 · Artificial Intelligence

From Deep Learning to Large‑Model OCR: Which Model Leads the Pack?

This article traces OCR's evolution from early CNN‑LSTM systems to modern multimodal VLMs, analyzes leading open‑source models such as DeepSeek‑OCR, PaddleOCR, and MonkeyOCR, and offers practical guidance for long‑document, academic, and edge‑computing scenarios.

DeepSeek-OCRMonkeyOCROCR

0 likes · 15 min read

From Deep Learning to Large‑Model OCR: Which Model Leads the Pack?