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).
Standard Thinking's decision model. Ministral 3 8B with a merged LoRA, served through stock SGLang and an open jev-adapter that exposes /v1/systemone and scores the supplied options in one forward pass with per-type temperatures.
Decides
choice, score, noul
choice, score, noul, classify, route
Architecture
blocks-of-experts
standard-one
Fine-tuned from
qwen/qwen3.8-27b
mistralai/ministral-3-8b-instruct-2512-bf16
License
apache-2.0
apache-2.0
Availability
Open weights
Open weights + hosted API
Hosted by
—
Standard Thinking
Input price
—
—
Decision accuracy
88.7%
71.1%
Calibration error
—
—
Valid action rate
—
—
Median latency
137 ms
25.8 ms
p95 latency
—
41.9 ms
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 standard-one?
jev-27b is from AutoTrust AI Lab and standard-one from Standard Thinking. jev-27b has open weights you can download and run; standard-one has open weights and a hosted API. Both answer choice, score and noul questions. Only standard-one answers classify and route. standard-one is the smaller model, at 8.0B parameters to 27B.
Which is more accurate, jev-27b or standard-one?
They report on different suites — jev-27b 88.7% on JevBench public set (231 items), family-macro score, maker's run, standard-one 71.1% on typed-decisions suite, 400 cases / 2,000 decisions (maker's served run, v2) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, jev-27b or standard-one?
jev-27b: Free (open weights). standard-one: Hosted, price not published, or free to self-host. Open weights cost nothing per call beyond your own hardware.
Which is faster, jev-27b or standard-one?
By their publishers’ figures, standard-one answers in about 25.8 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 standard-one locally?
Yes, both: systemone pull autotrust-ai/jev-27b and systemone pull standard-thinking/standard-one download the weights.
Evaluation suite
JevBench public set (231 items), family-macro score, maker's run
