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.
Small open typed-decision model with calibrated probabilities, first-class Nepali coverage.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
jebadiah
mira
Fine-tuned from
qwen/qwen3.8-27b
jhu-clsp/mmbert-small
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
86.6%
74.5%
Calibration error
0.113
0.025
Valid action rate
—
100.0%
Median latency
—
30 ms
p95 latency
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43 ms
Evaluation suite
JevBench public set (231 items), maker's run with the v1.4.2 harness; ECE on the hard tier
s1-decision-bench
Latest version
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 jebadiah and mira?
jebadiah is from Frontier Infra and mira from SAGEA. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions.
Which is more accurate, jebadiah or mira?
They report on different suites — jebadiah 86.6% on JevBench public set (231 items), maker's run with the v1.4.2 harness; ECE on the hard tier, mira 74.5% on s1-decision-bench — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, jebadiah or mira?
jebadiah: Free (open weights). mira: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run jebadiah or mira locally?
Yes, both: systemone pull frontier-infra/jebadiah and systemone pull sagea/mira download the weights.
