Xberg is a single engine for detecting, reading, OCR’ing, and extracting text, tables, metadata, and structured data from over 100 document formats and 115 file extensions. It offers transcription, embeddings, layout reconstruction, schema-driven JSON extraction, and code intelligence via language bindings in Rust, Python, Go, Java, and more. You can run it as a library, CLI, REST API, or MCP server with configurable Cargo features.

Datalab’s 4 billion-parameter Chandra OCR 2 outperforms GPT-4o and Gemini across independent and multilingual benchmarks, handling complex layouts, math notation, flowcharts and 90 languages with state-of-the-art accuracy. It’s available under Apache 2.0 code with a modified OpenRAIL-M license for weights, runs locally via HuggingFace or vLLM, and doubles throughput over its predecessor.

Chandra OCR 2, a 4 billion-parameter model from Datalab, outperforms GPT-4o and Gemini on AllenAI’s olmOCR benchmark and a 90-language test while halving the model size. It preserves layout, reads complex tables and math notation, converts diagrams to Mermaid, and runs at two pages per second on an NVIDIA H100. The code is Apache 2.0 but the model weights use an OpenRAIL-M license with commercial restrictions.