DeepSeek-OCR is an inference repository for a multimodal OCR model that combines vision encoders (SAM and CLIP) with a large language model (DeepSeek-V2/V3) to perform optical character recognition with layout awareness, supporting native and dynamic resolution processing. The system provides two inference paths: a Hugging Face Transformers integration for simple usage and a custom vLLM integration for high-throughput batched inference, including PDF processing and evaluation benchmarks. The architecture is a monolithic model definition with separate modules for vision encoding (deepencoder), image preprocessing (process), and vLLM glue code, all tightly coupled to the specific model architecture. The codebase is functional and demonstrates competent engineering for research-grade inference, but lacks production hardening, documentation, and consistent coding standards.