Three open models, from 17M to 68M parameters, built for a single job: finding personal information in text accurately enough for production and fast enough to run on every request.

Highlights

88.3% F1 on Privacy-Bench , a benchmark of human-annotated business documents, with a 68M-parameter model. PII-Tracer (596M) scores 86.5%, GLiNER2-PII (205M) 83.7% and nvidia GLiNER-PII (570M) 66.4%.

The smallest model, at 17M parameters, is within half a point of PII-Tracer at 1/35 of its size.

37% fewer false alarms than PII-Tracer while finding almost as much personal data.

12 types of PII , from names and emails to government IDs, secrets and IP addresses.

Openly available on Hugging Face under Apache-2.0: pii-extractor-68M , pii-extractor-32M and pii-extractor-17M .

Every message sent to an LLM, every document added to a search index and every support ticket written to a log raises the same question: does this contain personal information, and exactly where?…