Hanno Labs' small calibrated decision model. A LoRA on Qwen3-1.7B plus trained decision-token embeddings with stable slots, returning the full distribution over up to 255 caller-defined choices and a null slot for Choice, Score and Noul questions.
An independent Jev-shaped reproduction on DeBERTa-v3-large. One state and any number of choice, score and yes/no questions go in, and a calibrated distribution per question comes out of one forward pass. Public gold labels only.
Decides
choice, score, noul, classify, route
choice, score, noul, classify
Architecture
bosun
open-jev
Fine-tuned from
qwen/qwen3-1.7b
microsoft/deberta-v3-large
License
apache-2.0
apache-2.0
Availability
Open weights
Open weights
Hosted by
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Input price
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Decision accuracy
84.9%
85.4%
Calibration error
0.050
0.022
Valid action rate
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Median latency
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28 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 bosun and open-jev-deberta-v3-large?
bosun is from Hanno Labs and open-jev-deberta-v3-large from Kotoba Labs. Both have open weights you can download and run. Both answer choice, score, noul and classify questions. Only bosun answers route. open-jev-deberta-v3-large is the smaller model, at 434M parameters to 2.0B.
Which is more accurate, bosun or open-jev-deberta-v3-large?
They report on different suites — bosun 84.9% on DecisionBench (Hanno-Labs/decision-bench, 23,900 rows; seen task families), open-jev-deberta-v3-large 85.4% on Kotoba held-out test, seen question types (banking77, SST-5, BoolQ) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, bosun or open-jev-deberta-v3-large?
bosun: Free (open weights). open-jev-deberta-v3-large: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run bosun or open-jev-deberta-v3-large locally?
Yes, both: systemone pull hanno-labs/bosun and systemone pull kotoba-labs/open-jev-deberta-v3-large download the weights.
Evaluation suite
DecisionBench (Hanno-Labs/decision-bench, 23,900 rows; seen task families)
Kotoba held-out test, seen question types (banking77, SST-5, BoolQ)
