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.
Metask Lab's calibrated decision model in 16 languages. Qwen3.5-4B with a merged LoRA trained with the Nimble candidate-logit objective; one forward pass and a softmax over at most 26 answer-letter logits, with one temperature per question type.
Decides
choice, score, noul, classify, extract, route
choice, score, noul, classify, route
Architecture
gliner2
metask-jev
Fine-tuned from
fastino/gliner2-large-v1
qwen/qwen3.5-4b
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%
80.1%
Calibration error
—
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Valid action rate
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Median latency
38.3 ms
62.8 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 metask-jev?
gliner2-5-decide is from Fastino Labs and metask-jev from Metask Lab. gliner2-5-decide has open weights and a hosted API; metask-jev 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 4.5B.
Which is more accurate, gliner2-5-decide or metask-jev?
They report on different suites — gliner2-5-decide 60.2% on Fastino fast-decisions suite (17 datasets), metask-jev 80.1% on JevBench v1.2 public set (231 items) at 4,096 tokens, maker's run — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, gliner2-5-decide or metask-jev?
gliner2-5-decide: Hosted, price not published, or free to self-host. metask-jev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, gliner2-5-decide or metask-jev?
By their publishers’ figures, gliner2-5-decide answers in about 38.3 ms at the median and metask-jev in about 62.8 ms — measured on different hardware, so treat it as a rough guide.
Can I run gliner2-5-decide or metask-jev locally?
Yes, both: systemone pull fastino-labs/gliner2-5-decide and systemone pull metask-lab/metask-jev download the weights.
Evaluation suite
Fastino fast-decisions suite (17 datasets)
JevBench v1.2 public set (231 items) at 4,096 tokens, maker's run
