An open family of System One models. A LoRA adapter plus a pointer head on a frozen Qwen base returns a distribution per typed question in one forward pass, serves TypeSafe's /v1/systemone contract, and ships a fitted temperature with every checkpoint.
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, route
choice, score, noul, classify, route
Architecture
kev
simple-jev
Fine-tuned from
qwen/qwen3.5-4b-base
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
83.8%
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Calibration error
0.042
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Valid action rate
—
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Median latency
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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 kev and simple-jev?
kev is from Jared Palmer and simple-jev from Featherless AI. kev has open weights you can download and run; simple-jev has open weights and a hosted API. Both answer choice, score, noul, classify and route questions.
Which is more accurate, kev or simple-jev?
Only kev publishes an accuracy figure (83.8% on transfer-v4 (locked, out of domain)); simple-jev does not, so there is no comparison to make without your own test.
Which is cheaper, kev or simple-jev?
kev: 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 kev or simple-jev locally?
Yes, both: systemone pull jared-palmer/kev and systemone pull featherless-ai/simple-jev download the weights.
