Fastino releases 340M open-weight decision model GLiNER2.5-Decide, tops 9 of 17 benchmarks
vanstriendaniel · x · 2026-09-25
Fastino introduced GLiNER2.5-Decide, a 340M-parameter open-weight encoder-based decision model built for fast, deterministic classification. It jointly decodes user-defined typed questions and rules, returning structured decisions with probability distributions and confidence scores.
On Fast Decisions, an internal benchmark of 17 datasets covering routing, triage, classification, sentiment, and content understanding, the model leads on 9 of 17 datasets with the highest average score of 60.1%, ahead of SemIf (56.4%), JevK5 (57.5%), and Laya (46.6%). The team positions it for tool calling, model routing, and browser agent use cases.
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