An open Jev-style LoRA on Qwen3.5-9B from Bespoke Labs, trained on 2,676 contrastively curated examples to score the allowed answer tokens directly for enums, booleans and rubric levels. Recipe, data and a public benchmark suite are released with it.
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, noul, score, classify, route
choice, score, noul
Architecture
nimble
blocks-of-experts
Fine-tuned from
qwen/qwen3.5-9b
qwen/qwen3.8-27b
License
apache-2.0
apache-2.0
Availability
Open weights + hosted API
Open weights
Hosted by
Bespoke Labs
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Input price
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Decision accuracy
90.1%
88.7%
Calibration error
0.054
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Valid action rate
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Median latency
106 ms
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 bespoke-nimble-9b and jev-27b?
bespoke-nimble-9b is from Bespoke Labs and jev-27b from AutoTrust AI Lab. bespoke-nimble-9b has open weights and a hosted API; jev-27b has open weights you can download and run. Both answer choice, noul and score questions. Only bespoke-nimble-9b answers classify and route. bespoke-nimble-9b is the smaller model, at 9.0B parameters to 27B.
Which is more accurate, bespoke-nimble-9b or jev-27b?
They report on different suites — bespoke-nimble-9b 90.1% on Bespoke held-out set (324 examples), jev-27b 88.7% on JevBench public set (231 items), family-macro score, maker's run — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, bespoke-nimble-9b or jev-27b?
bespoke-nimble-9b: Hosted, price not published, or free to self-host. jev-27b: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, bespoke-nimble-9b or jev-27b?
By their publishers’ figures, bespoke-nimble-9b answers in about 106 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 bespoke-nimble-9b or jev-27b locally?
Yes, both: systemone pull bespoke-labs/bespoke-nimble-9b and systemone pull autotrust-ai/jev-27b download the weights.
Evaluation suite
Bespoke held-out set (324 examples)
JevBench public set (231 items), family-macro score, maker's run
