LlamaIndex releases OCRia-1, topping ParseBench at 87.4 with 2-4x faster decoding
llama_index · x · 2026-10-26
LlamaIndex released OCRia-1, a frontier VLM for document parsing claiming SOTA in accuracy, cost, and latency. It scores 87.4 on ParseBench and leads three third-party benchmarks: olmOCR-bench (83.5 overall, 92.9 on tables), PulseBench-Tab (84.1), and fr-bench-pdf2md (72.1).
It excels at complex tables (nested headers, merged cells, scanned grids) and unlabeled charts while preserving formatting, and decodes 2-4x+ faster than recent open-weight models. A 37-page technical report details the data/training pipeline, with a 24-page appendix of experimental findings for those building their own vision models.
Related event: LlamaIndex Releases OCRia-1, Setting New SOTA in Document Parsing(2 posts)→
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