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.
Frontier Infra's open decision model. A LoRA merged into Qwen3.8-27B (thinking off) that answers one typed question per forward pass with a probability over the option labels, served through AINode's TypeSafe-compatible /v1/systemone.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
d1
jebadiah
Fine-tuned from
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qwen/qwen3.8-27b
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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86.6%
Calibration error
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0.113
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 jebadiah?
d1 is from Liquid AI and jebadiah from Frontier Infra. d1 is only available as a hosted API; jebadiah has open weights you can download and run. Both answer choice, score, noul, classify and route questions. d1 is licensed proprietary; jebadiah, apache-2.0.
Which is more accurate, d1 or jebadiah?
Only jebadiah publishes an accuracy figure (86.6% on JevBench public set (231 items), maker's run with the v1.4.2 harness; ECE on the hard tier); d1 does not, so there is no comparison to make without your own test.
Which is cheaper, d1 or jebadiah?
d1: Hosted, price not published. jebadiah: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run d1 or jebadiah locally?
jebadiah yes — systemone pull frontier-infra/jebadiah downloads its weights. The other is only served as a hosted API.
Evaluation suite
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JevBench public set (231 items), maker's run with the v1.4.2 harness; ECE on the hard tier
