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.
A local, Jev-compatible decision model from Rizzo AI Academy. XHToken's Spark-X2.5-4B with a merged typed-decisions LoRA, run on llama.cpp; yes/no, choice and score questions share one prefill of the state and are read from the answer-letter logits. No text is generated.
Decides
choice, score, noul, classify, extract, route
choice, score, noul, classify, route
Architecture
gliner2
rizzo-flow
Fine-tuned from
fastino/gliner2-large-v1
xhtoken/spark-x2.5-4b
License
apache-2.0
apache-2.0
Availability
Open weights + hosted API
Open weights
Hosted by
Fastino
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Input price
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Decision accuracy
60.2%
64.8%
Calibration error
—
0.112
Valid action rate
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Median latency
38.3 ms
195 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 gliner2-5-decide and rizzo-flow?
gliner2-5-decide is from Fastino Labs and rizzo-flow from Rizzo AI Academy. gliner2-5-decide has open weights and a hosted API; rizzo-flow has open weights you can download and run. Both answer choice, score, noul, classify and route questions. Only gliner2-5-decide answers extract. gliner2-5-decide is the smaller model, at 340M parameters to 4.0B.
Which is more accurate, gliner2-5-decide or rizzo-flow?
They report on different suites — gliner2-5-decide 60.2% on Fastino fast-decisions suite (17 datasets), rizzo-flow 64.8% on LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions), Q8_0 — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, gliner2-5-decide or rizzo-flow?
gliner2-5-decide: Hosted, price not published, or free to self-host. rizzo-flow: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, gliner2-5-decide or rizzo-flow?
By their publishers’ figures, gliner2-5-decide answers in about 38.3 ms at the median and rizzo-flow in about 195 ms — measured on different hardware, so treat it as a rough guide.
Can I run gliner2-5-decide or rizzo-flow locally?
Yes, both: systemone pull fastino-labs/gliner2-5-decide and systemone pull rizzo-ai-academy/rizzo-flow download the weights.
Evaluation suite
Fastino fast-decisions suite (17 datasets)
LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions), Q8_0
