r/MachineLearning paid attention because the benchmark did not just crown a winner. It argued that many teams are overpaying for document extraction, then backed that claim with repeated runs, cost-per-success numbers, and a leaderboard where several cheaper models outperformed pricey defaults.
A LocalLLaMA post points to IBM's Granite-4.0-3B-Vision, a compact VLM built for charts, tables, and document key-value extraction rather than generic multimodal chat.
A post on r/LocalLLaMA highlighted Kreuzberg v4.5, a Rust-based document intelligence framework that now adds stronger layout and table understanding. The release claims Docling-level quality with lower memory overhead and materially faster processing.