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.
Juspay's open decision model. Qwen3.6-35B-A3B with a merged rank-16 LoRA, shipped with a pinned SGLang serving bundle that answers Choice, Score and Noul questions over text, images or a video through a TypeSafe-compatible /v1/systemone API.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
d1
xor
Fine-tuned from
—
qwen/qwen3.6-35b-a3b
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
—
90.0%
Calibration error
—
0.073
Valid action rate
—
—
Median latency
—
69 ms
p95 latency
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162 ms
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 d1 and xor?
d1 is from Liquid AI and xor from Juspay. d1 is only available as a hosted API; xor has open weights you can download and run. Both answer choice, score, noul, classify and route questions. d1 is licensed proprietary; xor, apache-2.0.
Which is more accurate, d1 or xor?
Only xor publishes an accuracy figure (90.0% on JevBench public set (231 items), maker's self-run of Xor 1.2); d1 does not, so there is no comparison to make without your own test.
Which is cheaper, d1 or xor?
d1: Hosted, price not published. xor: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run d1 or xor locally?
xor yes — systemone pull juspay/xor downloads its weights. The other is only served as a hosted API.
JevBench public set (231 items), maker's self-run of Xor 1.2
