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.
Invergent's decision model for text and images. A fine-tune of Gemma-4-26B-A4B (about 4B parameters active per token) that answers Choice, Noul and Score questions, with an optional thinking mode for harder questions.
Decides
choice, score, noul, classify, extract, route
choice, score, noul, classify, route
Architecture
gliner2
rune
Fine-tuned from
fastino/gliner2-large-v1
google/gemma-4-26b-a4b-it
License
apache-2.0
apache-2.0
Availability
Open weights + hosted API
Open weights + hosted API
Hosted by
Fastino
Invergent
Input price
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Decision accuracy
60.2%
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Calibration error
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Valid action rate
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Median latency
38.3 ms
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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 rune?
gliner2-5-decide is from Fastino Labs and rune from Surogate (Invergent). Both have open weights and a hosted API. 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 26B.
Which is more accurate, gliner2-5-decide or rune?
Only gliner2-5-decide publishes an accuracy figure (60.2% on Fastino fast-decisions suite (17 datasets)); rune does not, so there is no comparison to make without your own test.
Which is cheaper, gliner2-5-decide or rune?
gliner2-5-decide: Hosted, price not published, or free to self-host. rune: Hosted, price not published, or free to self-host. Open weights cost nothing per call beyond your own hardware.
Can I run gliner2-5-decide or rune locally?
Yes, both: systemone pull fastino-labs/gliner2-5-decide and systemone pull surogate/rune download the weights.
