The first System One model. Reads a state, answers typed Choice, Score and Noul questions in one call with calibrated probabilities, and generates no text. Closed weights, served by TypeSafe AI.
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).
Decides
choice, score, noul, classify, route
choice, score, noul
Architecture
jev
blocks-of-experts
Fine-tuned from
—
qwen/qwen3.8-27b
License
proprietary
apache-2.0
Availability
Hosted API
Open weights
Hosted by
TypeSafe AI
—
Input price
$0.042/MTok
—
Decision accuracy
—
88.7%
Calibration error
—
—
Valid action rate
—
—
Median latency
—
137 ms
p95 latency
—
—
Evaluation suite
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 and jev-27b?
jev is from TypeSafe AI and jev-27b from AutoTrust AI Lab. jev is only available as a hosted API; jev-27b has open weights you can download and run. Both answer choice, score and noul questions. Only jev answers classify and route. jev is licensed proprietary; jev-27b, apache-2.0.
Which is more accurate, jev or jev-27b?
Only jev-27b publishes an accuracy figure (88.7% on JevBench public set (231 items), family-macro score, maker's run); jev does not, so there is no comparison to make without your own test.
Which is cheaper, jev or jev-27b?
jev: $0.042 / $0 per 1M. jev-27b: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run jev or jev-27b locally?
jev-27b yes — systemone pull autotrust-ai/jev-27b downloads its weights. The other is only served as a hosted API.
—
JevBench public set (231 items), family-macro score, maker's run
