Ruoxi Qiu's decision adapter for a frozen Qwen3.8-27B: a 6.3M-parameter LoRA on the last four text layers plus a numerical prior. One shared state feeds isolated question branches; each Choice, Noul or Score question returns probabilities with no generated tokens.
Fastino's open-weight decision model. A DeBERTa-v3-large encoder that scores label sets supplied at runtime, answers single-label, multi-label, yes/no and ordinal questions in one pass, and extracts spans and relations.
Decides
choice, noul, score
choice, score, noul, classify, extract, route
Architecture
canopy-jev
gliner2
Fine-tuned from
qwen/qwen3.8-27b
fastino/gliner2-large-v1
License
apache-2.0
apache-2.0
Availability
Open weights
Open weights + hosted API
Hosted by
—
Fastino
Input price
—
—
Decision accuracy
87.4%
60.2%
Calibration error
—
—
Valid action rate
—
—
Median latency
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38.3 ms
p95 latency
—
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Figures are from each model’s manifest; accuracy and latency are what the publishers report, on their own suites and hardware. Add a third model.
Questions
What is the difference between canopy-jev and gliner2-5-decide?
canopy-jev is from Ruoxi Qiu and gliner2-5-decide from Fastino Labs. canopy-jev has open weights you can download and run; gliner2-5-decide has open weights and a hosted API. Both answer choice, noul and score questions. Only gliner2-5-decide answers classify, extract and route. gliner2-5-decide is the smaller model, at 340M parameters to 27B.
Which is more accurate, canopy-jev or gliner2-5-decide?
They report on different suites — canopy-jev 87.4% on JevBench public set (231 items; 202 correct), the maker's own fresh zero-shot run with the upstream scorer, gliner2-5-decide 60.2% on Fastino fast-decisions suite (17 datasets) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, canopy-jev or gliner2-5-decide?
canopy-jev: Free (open weights). gliner2-5-decide: Hosted, price not published, or free to self-host. Open weights cost nothing per call beyond your own hardware.
Can I run canopy-jev or gliner2-5-decide locally?
Yes, both: systemone pull camellia86/canopy-jev and systemone pull fastino-labs/gliner2-5-decide download the weights.
Evaluation suite
JevBench public set (231 items; 202 correct), the maker's own fresh zero-shot run with the upstream scorer
