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.
An open family of System One models. A LoRA adapter plus a pointer head on a frozen Qwen base returns a distribution per typed question in one forward pass, serves TypeSafe's /v1/systemone contract, and ships a fitted temperature with every checkpoint.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
d1
kev
Fine-tuned from
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qwen/qwen3.5-4b-base
License
proprietary
apache-2.0
Availability
Hosted API
Open weights
Hosted by
Liquid AI
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Input price
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Decision accuracy
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83.8%
Calibration error
—
0.042
Valid action rate
—
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Median latency
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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 d1 and kev?
d1 is from Liquid AI and kev from Jared Palmer. d1 is only available as a hosted API; kev has open weights you can download and run. Both answer choice, score, noul, classify and route questions. d1 is licensed proprietary; kev, apache-2.0.
Which is more accurate, d1 or kev?
Only kev publishes an accuracy figure (83.8% on transfer-v4 (locked, out of domain)); d1 does not, so there is no comparison to make without your own test.
Which is cheaper, d1 or kev?
d1: Hosted, price not published. kev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run d1 or kev locally?
kev yes — systemone pull jared-palmer/kev downloads its weights. The other is only served as a hosted API.
