DharmaOCR: Open-Source Specialized SLM (3B) + Cost–Performance Benchmark against LLMs and other open-sourced models [R]

**DharmaOCR** is an open-source OCR system built by fine-tuning 3B and 7B SLMs via SFT + DPO, achieving accuracy scores of 0.911 and 0.925 respectively — outperforming GPT-4.5, Gemini 2.1 Pro, Claude Opus 4.6, and open-source alternatives including OlmOCR and Qwen3 on their benchmark. The use of DPO with the model's own degenerate outputs as negative examples reduced failure rate by 87.6%, offering a practical recipe for improving OCR reliability without larger models. AWQ quantization further cuts per-page inference cost by ~22% with negligible accuracy loss, making the 3B variant a cost-efficient option for production document processing pipelines.