A 0.6B decision model on Qwen3-0.6B-Base from the DocsGPT team. Give it a state and typed questions (yes/no, a choice of up to 16 options, a 3- or 4-level score) and it returns calibrated probabilities in one pass, for RAG and agent checks.
Uprelic's hosted decision API, run on GPUs in Paris. Answers noul, choice and score questions about text, JSON and up to 8 images, with a probability for every option and no generated text, on the same request shape as Jev. No weights; base model and size not disclosed.
Decides
choice, score, noul, classify, rank, route
choice, score, noul, classify, route
Architecture
arc-decide
strom
Fine-tuned from
qwen/qwen3-0.6b-base
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License
mit
proprietary
Availability
Open weights
Hosted API
Hosted by
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Uprelic
Input price
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$0.042/MTok
Decision accuracy
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87.0%
Calibration error
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0.033
Valid action rate
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Median latency
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136 ms
p95 latency
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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 arc-decide and strom?
arc-decide is from Arc53 and strom from Uprelic. arc-decide has open weights you can download and run; strom is only available as a hosted API. Both answer choice, score, noul, classify and route questions. Only arc-decide answers rank. arc-decide is licensed mit; strom, proprietary.
Which is more accurate, arc-decide or strom?
Only strom publishes an accuracy figure (87.0% on JevBench public set (231 items), the maker's production run of Strom 1.0.7 on 1 Oct 2026 (Open-Jev harness format)); arc-decide does not, so there is no comparison to make without your own test.
Which is cheaper, arc-decide or strom?
arc-decide: Free (open weights). strom: $0.042 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Can I run arc-decide or strom locally?
arc-decide yes — systemone pull arc53/arc-decide downloads its weights. The other is only served as a hosted API.
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JevBench public set (231 items), the maker's production run of Strom 1.0.7 on 1 Oct 2026 (Open-Jev harness format)
