  The vast portion of workloads employing LLMs involves answering questions
grounded on PDF or scan content. We introduce the Arctic-TILT achieving
accuracy on par with models 1000$\times$ its size on these use cases. It can be
fine-tuned and deployed on a single 24GB GPU, lowering operational costs while
processing Visually Rich Documents with up to 400k tokens. The model
establishes state-of-the-art results on seven diverse Document Understanding
benchmarks, as well as provides reliable confidence scores and quick inference,
which are essential for processing files in large-scale or time-sensitive
enterprise environments.
