An independent Jev-shaped reproduction on DeBERTa-v3-large. One state and any number of choice, score and yes/no questions go in, and a calibrated distribution per question comes out of one forward pass. Public gold labels only.
Featherless AI's open server that turns a stock Hugging Face language model into a typed-decision endpoint. It reads the next-token logits for each question and builds the Choice, Score or Noul answer itself; no classifier head is trained and no JSON is generated.
Decides
choice, score, noul, classify
choice, score, noul, classify, route
Architecture
open-jev
simple-jev
Fine-tuned from
microsoft/deberta-v3-large
google/gemma-4-26b-a4b-it
License
apache-2.0
apache-2.0
Availability
Open weights
Open weights + hosted API
Hosted by
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Featherless AI
Input price
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Decision accuracy
85.4%
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Calibration error
0.022
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Valid action rate
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Median latency
28 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 open-jev-deberta-v3-large and simple-jev?
open-jev-deberta-v3-large is from Kotoba Labs and simple-jev from Featherless AI. open-jev-deberta-v3-large has open weights you can download and run; simple-jev has open weights and a hosted API. Both answer choice, score, noul and classify questions. Only simple-jev answers route.
Which is more accurate, open-jev-deberta-v3-large or simple-jev?
Only open-jev-deberta-v3-large publishes an accuracy figure (85.4% on Kotoba held-out test, seen question types (banking77, SST-5, BoolQ)); simple-jev does not, so there is no comparison to make without your own test.
Which is cheaper, open-jev-deberta-v3-large or simple-jev?
open-jev-deberta-v3-large: Free (open weights). simple-jev: Hosted, price not published, or free to self-host. Open weights cost nothing per call beyond your own hardware.
Can I run open-jev-deberta-v3-large or simple-jev locally?
Yes, both: systemone pull kotoba-labs/open-jev-deberta-v3-large and systemone pull featherless-ai/simple-jev download the weights.
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Evaluation suite
Kotoba held-out test, seen question types (banking77, SST-5, BoolQ)
