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.
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.
Decides
choice, noul, score, classify, route
choice, score, noul, classify, route
Architecture
nimble
d1
Fine-tuned from
qwen/qwen3.5-9b
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License
apache-2.0
proprietary
Availability
Open weights + hosted API
Hosted API
Hosted by
Bespoke Labs
Liquid AI
Input price
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Decision accuracy
90.1%
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Calibration error
0.054
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Valid action rate
—
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Median latency
106 ms
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p95 latency
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Evaluation suite
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 d1?
bespoke-nimble-9b is from Bespoke Labs and d1 from Liquid AI. bespoke-nimble-9b has open weights and a hosted API; d1 is only available as a hosted API. Both answer choice, noul, score, classify and route questions. bespoke-nimble-9b is licensed apache-2.0; d1, proprietary.
Which is more accurate, bespoke-nimble-9b or d1?
Only bespoke-nimble-9b publishes an accuracy figure (90.1% on Bespoke held-out set (324 examples)); d1 does not, so there is no comparison to make without your own test.
Which is cheaper, bespoke-nimble-9b or d1?
bespoke-nimble-9b: Hosted, price not published, or free to self-host. d1: Hosted, price not published. Open weights cost nothing per call beyond your own hardware.
Can I run bespoke-nimble-9b or d1 locally?
bespoke-nimble-9b yes — systemone pull bespoke-labs/bespoke-nimble-9b downloads its weights. The other is only served as a hosted API.
