Liquid AI's first decision model, served only through the Liquid API. Returns Choice, Score and Noul answers with probability distributions and zero output tokens, on the /v1/systemone request shape used by TypeSafe's SDK.
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
d1
blocks-of-experts
Fine-tuned from
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qwen/qwen3.8-27b
License
proprietary
apache-2.0
Availability
Hosted API
Open weights
Hosted by
Liquid AI
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Input price
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Decision accuracy
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88.7%
Calibration error
—
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Valid action rate
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Median latency
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137 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 d1 and jev-27b?
d1 is from Liquid AI and jev-27b from AutoTrust AI Lab. d1 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 d1 answers classify and route. d1 is licensed proprietary; jev-27b, apache-2.0.
Which is more accurate, d1 or jev-27b?
Only jev-27b publishes an accuracy figure (88.7% on JevBench public set (231 items), family-macro score, maker's run); d1 does not, so there is no comparison to make without your own test.
Which is cheaper, d1 or jev-27b?
d1: Hosted, price not published. jev-27b: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run d1 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.
Evaluation suite
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JevBench public set (231 items), family-macro score, maker's run
