A rank-16 LoRA on Qwen3.5-4B built for the JevBench setting. A document, a policy and a question go in; a calibrated distribution over the option letters comes out of one forward pass. Research and demo use only.
A Thai-and-English System One model. Qwen3.5-0.8B continued-pretrained on about 5B Thai tokens, its language-model head replaced by a 256-way slot head (slot 255 abstains), trained on 2–3M decision examples and temperature-calibrated per question type.
Decides
choice, score, noul, classify
choice, score, noul, classify, route
Architecture
hopper
openthai
Fine-tuned from
qwen/qwen3.5-4b
qwen/qwen3.5-0.8b-base
License
Research and demo use only (training data includes RACE, non-commercial); serving code 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
68.5%
74.3%
Calibration error
0.102
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Valid action rate
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Median latency
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40 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 hopper and openthai-systemone?
hopper is from HopitAI and openthai-systemone from iApp Technology. Both have open weights you can download and run. Both answer choice, score, noul and classify questions. Only openthai-systemone answers route. openthai-systemone is the smaller model, at 800M parameters to 4.0B. hopper is licensed other; openthai-systemone, apache-2.0.
Which is more accurate, hopper or openthai-systemone?
They report on different suites — hopper 68.5% on JevBench public hard tier (111 items, measured by the authors), openthai-systemone 74.3% on Bespoke public subsets (13, macro average) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, hopper or openthai-systemone?
hopper: Free (open weights). openthai-systemone: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run hopper or openthai-systemone locally?
Yes, both: systemone pull hopit-ai/hopper and systemone pull iapp-technology/openthai-systemone download the weights.
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Evaluation suite
JevBench public hard tier (111 items, measured by the authors)
