# A Deployability Study Puts Nine On-Device Entity Recognizers Against Latency and Output Validity

The comparison spans spaCy, GLiNER encoders and locally run Qwen3 and DeepSeek-R1 models from 13 million to 8 billion parameters, scored partly against labels built by a cross-family judge panel.

- Published: 2026-10-02T06:31:19.109Z
- Canonical: https://polylog.news/ai/2026-10-02/a-deployability-study-puts-nine-on-device-entity-recognizers
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [arXiv cs.CL](https://arxiv.org/abs/2610.00007)

A new study argues that the question for on-device extraction is not leaderboard accuracy but whether a model is deployable at all. The paper evaluates nine systems across three paradigms and a parameter range from 13 million to 8 billion:…

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