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.
FLock.io's typed-decision model, fine-tuned from Mapika's decider-2b. Reads one hidden state per question and scores the declared options, so an answer outside the list cannot occur; several questions about one state share a forward pass.
Decides
choice, score, noul, classify, route
choice, score, noul
Architecture
d1
this-that
Fine-tuned from
—
mapika/decider
License
proprietary
mit
Availability
Hosted API
Open weights
Hosted by
Liquid AI
—
Input price
—
—
Decision accuracy
—
87.8%
Calibration error
—
—
Valid action rate
—
—
Median latency
—
31.4 ms
p95 latency
—
—
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 this-that-model?
d1 is from Liquid AI and this-that-model from FLock.io. d1 is only available as a hosted API; this-that-model has open weights you can download and run. Both answer choice, score and noul questions. Only d1 answers classify and route. d1 is licensed proprietary; this-that-model, mit.
Which is more accurate, d1 or this-that-model?
Only this-that-model publishes an accuracy figure (87.8% on limberc/this-that-complex-decisions (1,710 questions, FLock's benchmark)); d1 does not, so there is no comparison to make without your own test.
Which is cheaper, d1 or this-that-model?
d1: Hosted, price not published. this-that-model: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run d1 or this-that-model locally?
this-that-model yes — systemone pull flock-io/this-that-model downloads its weights. The other is only served as a hosted API.
