AutoTrust's student of TypeSafe Jev 1.13. A frozen Qwen3.8-27B plus a 108.9M-parameter decision block trained on Jev's own output distributions; one set of weights answers typed questions in one pass (System 1) or generates text with the untouched base (System 2).
An embedding model turned decision model. Qwen3-Embedding-4B with a merged LoRA, driven by the open JevEmbed toolkit, which scores Choice, Score and Noul questions from embedding similarity and returns a distribution without generating text.
Decides
choice, score, noul
choice, score, noul, classify
Architecture
blocks-of-experts
jevembed
Fine-tuned from
qwen/qwen3.8-27b
qwen/qwen3-embedding-4b
License
apache-2.0
apache-2.0
Availability
Open weights
Open weights
Hosted by
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Input price
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Decision accuracy
88.7%
85.9%
Calibration error
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Valid action rate
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Median latency
137 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 jev-27b and jevembed?
jev-27b is from AutoTrust AI Lab and jevembed from HIT-TMG (Lychee Team). Both have open weights you can download and run. Both answer choice, score and noul questions. Only jevembed answers classify. jevembed is the smaller model, at 4.0B parameters to 27B.
Which is more accurate, jev-27b or jevembed?
They report on different suites — jev-27b 88.7% on JevBench public set (231 items), family-macro score, maker's run, jevembed 85.9% on JevEmbed-Data test split (64,110 hard-label questions), final LoRA checkpoint before merging — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, jev-27b or jevembed?
jev-27b: Free (open weights). jevembed: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run jev-27b or jevembed locally?
Yes, both: systemone pull autotrust-ai/jev-27b and systemone pull hit-tmg/jevembed download the weights.
Evaluation suite
JevBench public set (231 items), family-macro score, maker's run
JevEmbed-Data test split (64,110 hard-label questions), final LoRA checkpoint before merging
