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.
A multimodal decision classifier over text, image, audio and video on Gemma 4 12B, fine-tuned on 30,000 questions. Returns a probability per option and generates nothing.
Decides
choice, noul, score, classify, route
choice, noul, score, classify
Architecture
nimble
jev-omni
Fine-tuned from
qwen/qwen3.5-9b
google/gemma-4-12b-it
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%
87.6%
Calibration error
0.054
0.040
Valid action rate
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Median latency
106 ms
83 ms
p95 latency
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Evaluation suite
Bespoke held-out set (324 examples)
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-omni?
bespoke-nimble-9b is from Bespoke Labs and jev-omni from akhilaaa3. bespoke-nimble-9b has open weights and a hosted API; jev-omni has open weights you can download and run. Both answer choice, noul, score and classify questions. Only bespoke-nimble-9b answers route. bespoke-nimble-9b is the smaller model, at 9.0B parameters to 12B.
Which is more accurate, bespoke-nimble-9b or jev-omni?
They report on different suites — bespoke-nimble-9b 90.1% on Bespoke held-out set (324 examples), jev-omni 87.6% on DecisionBench Medium (author's set) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, bespoke-nimble-9b or jev-omni?
bespoke-nimble-9b: Hosted, price not published, or free to self-host. jev-omni: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, bespoke-nimble-9b or jev-omni?
By their publishers’ figures, jev-omni answers in about 83 ms at the median and bespoke-nimble-9b in about 106 ms — measured on different hardware, so treat it as a rough guide.
Can I run bespoke-nimble-9b or jev-omni locally?
Yes, both: systemone pull bespoke-labs/bespoke-nimble-9b and systemone pull akhilaaa3/jev-omni download the weights.
