A family of open System One models by Mark Marosi that softmax option-letter logits at an answer slot: decider-0.8b, 2b, 4b and 35b-a3b on Qwen3.5 bases, decider-12b on Gemma-4-12B-it, and training-free readouts of larger chat models. This page carries decider-2b v11.
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, route
choice, score, noul, classify, route
Architecture
decider
strom
Fine-tuned from
qwen/qwen3.5-2b-base
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License
apache-2.0
proprietary
Availability
Open weights
Hosted API
Hosted by
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Uprelic
Input price
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$0.042/MTok
Decision accuracy
75.2%
87.0%
Calibration error
—
0.033
Valid action rate
—
—
Median latency
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136 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 decider and strom?
decider is from Mapika and strom from Uprelic. decider 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. decider is licensed apache-2.0; strom, proprietary.
Which is more accurate, decider or strom?
They report on different suites — decider 75.2% on Decider regression set, 28 held-out tasks (decider-2b v11), strom 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) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, decider or strom?
decider: Free (open weights). strom: $0.042 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Can I run decider or strom locally?
decider yes — systemone pull mapika/decider downloads its weights. The other is only served as a hosted API.
