A local, Jev-compatible decision model from Rizzo AI Academy. XHToken's Spark-X2.5-4B with a merged typed-decisions LoRA, run on llama.cpp; yes/no, choice and score questions share one prefill of the state and are read from the answer-letter logits. No text is generated.
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
rizzo-flow
strom
Fine-tuned from
xhtoken/spark-x2.5-4b
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License
apache-2.0
proprietary
Availability
Open weights
Hosted API
Hosted by
—
Uprelic
Input price
—
$0.042/MTok
Decision accuracy
64.8%
87.0%
Calibration error
0.112
0.033
Valid action rate
—
—
Median latency
195 ms
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 rizzo-flow and strom?
rizzo-flow is from Rizzo AI Academy and strom from Uprelic. rizzo-flow 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. rizzo-flow is licensed apache-2.0; strom, proprietary.
Which is more accurate, rizzo-flow or strom?
They report on different suites — rizzo-flow 64.8% on LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions), Q8_0, 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, rizzo-flow or strom?
rizzo-flow: Free (open weights). strom: $0.042 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Which is faster, rizzo-flow or strom?
By their publishers’ figures, strom answers in about 136 ms at the median and rizzo-flow in about 195 ms — measured on different hardware, so treat it as a rough guide.
Can I run rizzo-flow or strom locally?
rizzo-flow yes — systemone pull rizzo-ai-academy/rizzo-flow downloads its weights. The other is only served as a hosted API.
LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions), Q8_0
JevBench public set (231 items), the maker's production run of Strom 1.0.7 on 1 Oct 2026 (Open-Jev harness format)
