An embedding model turned decision model. Qwen3-Embedding-4B with a merged LoRA, driven by the open JevEmbed toolkit, which scores Choice, Score and Noul questions from embedding similarity and returns a distribution without generating text.
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
choice, score, noul
Architecture
jevembed
this-that
Fine-tuned from
qwen/qwen3-embedding-4b
mapika/decider
License
apache-2.0
mit
Availability
Open weights
Open weights
Hosted by
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Input price
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Decision accuracy
85.9%
87.8%
Calibration error
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Valid action rate
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Median latency
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31.4 ms
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 jevembed and this-that-model?
jevembed is from HIT-TMG (Lychee Team) and this-that-model from FLock.io. Both have open weights you can download and run. Both answer choice, score and noul questions. Only jevembed answers classify. this-that-model is the smaller model, at 1.9B parameters to 4.0B. jevembed is licensed apache-2.0; this-that-model, mit.
Which is more accurate, jevembed or this-that-model?
They report on different suites — jevembed 85.9% on JevEmbed-Data test split (64,110 hard-label questions), final LoRA checkpoint before merging, this-that-model 87.8% on limberc/this-that-complex-decisions (1,710 questions, FLock's benchmark) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, jevembed or this-that-model?
jevembed: Free (open weights). this-that-model: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run jevembed or this-that-model locally?
Yes, both: systemone pull hit-tmg/jevembed and systemone pull flock-io/this-that-model download the weights.
Evaluation suite
JevEmbed-Data test split (64,110 hard-label questions), final LoRA checkpoint before merging
