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).
FLock.io's typed-decision model, fine-tuned from Mapika's decider-2b. Reads one hidden state per question and scores the declared options, so an answer outside the list cannot occur; several questions about one state share a forward pass.
Decides
choice, score, noul
choice, score, noul
Architecture
blocks-of-experts
this-that
Fine-tuned from
qwen/qwen3.8-27b
mapika/decider
License
apache-2.0
mit
Availability
Open weights
Open weights
Hosted by
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—
Input price
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Decision accuracy
88.7%
87.8%
Calibration error
—
—
Valid action rate
—
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Median latency
137 ms
31.4 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 jev-27b and this-that-model?
jev-27b is from AutoTrust AI Lab and this-that-model from FLock.io. Both have open weights you can download and run. Both answer choice, score and noul questions. this-that-model is the smaller model, at 1.9B parameters to 27B. jev-27b is licensed apache-2.0; this-that-model, mit.
Which is more accurate, jev-27b or this-that-model?
They report on different suites — jev-27b 88.7% on JevBench public set (231 items), family-macro score, maker's run, this-that-model 87.8% on limberc/this-that-complex-decisions (1,710 questions, FLock's benchmark) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, jev-27b or this-that-model?
jev-27b: Free (open weights). this-that-model: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, jev-27b or this-that-model?
By their publishers’ figures, this-that-model answers in about 31.4 ms at the median and jev-27b in about 137 ms — measured on different hardware, so treat it as a rough guide.
Can I run jev-27b or this-that-model locally?
Yes, both: systemone pull autotrust-ai/jev-27b and systemone pull flock-io/this-that-model download the weights.
Evaluation suite
JevBench public set (231 items), family-macro score, maker's run
