Unlimited-OCR — Krill mixed-nvfp4 (MLX)
A Mac-native (Apple Silicon / MLX) mixed-precision build of
baidu/Unlimited-OCR (built on
DeepSeek-OCR), packaged for the Krill
runtime. It parses documents and images to grounded text with no Python and
no trust_remote_code — the DeepSeek-MoE language backbone and the
DeepEncoder vision tower (SAM-ViT-B + CLIP-L + projector) run natively in
Swift + MLX.
Run with Krill
krill pull unlimited-ocr
krill run unlimited-ocr --image your_page.png "document parsing."
It emits grounded OCR, e.g.:
<|det|>title [48, 74, 402, 130]<|/det|>Invoice 2026
<|det|>text [33, 229, 370, 290]<|/det|>Bill to: Acme Corporation
...
Format
Mixed-precision, single-file model.safetensors (~2.3 GB, from the 6.67 GB bf16
source):
| Modules | Precision |
|---|---|
| MoE experts (the residency-dominant bulk) | nvfp4 (group 16) |
| attention q/k/v/o, dense + shared FFN, embed, lm_head | 8-bit affine (group 64) |
| DeepEncoder vision Linears (SAM / CLIP / projector) | 8-bit affine |
| Conv2d kernels, norms, position/learned embeddings, router gate | unquantized |
This format is Krill-specific (the native Swift+MLX runtime resolves the
per-module quantization); it is not a drop-in transformers checkpoint.
Scope
Ships the base view (single 1024 global view → 273 image tokens), which reads full pages including wide layouts. The "gundam" tiling mode (local crops for very dense/large scans) is a follow-up.
Credit & license
All credit to the original authors, baidu/Unlimited-OCR
and DeepSeek-OCR. MIT licensed, as upstream.
About this build
Quantized and tested by Sourav Singh for Krill, a Mac-native LLM runtime and coding agent in one Swift + MLX binary. More Apple Silicon builds: huggingface.co/srv-sngh. Notes on building with local models and frontier AI: souravailabs.ai · GitHub · LinkedIn · YouTube