An independent Jev-shaped reproduction on DeBERTa-v3-large. One state and any number of choice, score and yes/no questions go in, and a calibrated distribution per question comes out of one forward pass. Public gold labels only.
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
choice, score, noul, classify, route
Architecture
open-jev
strom
Fine-tuned from
microsoft/deberta-v3-large
—
License
apache-2.0
proprietary
Availability
Open weights
Hosted API
Hosted by
—
Uprelic
Input price
—
$0.042/MTok
Decision accuracy
85.4%
87.0%
Calibration error
0.022
0.033
Valid action rate
—
—
Median latency
28 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 open-jev-deberta-v3-large and strom?
open-jev-deberta-v3-large is from Kotoba Labs and strom from Uprelic. open-jev-deberta-v3-large has open weights you can download and run; strom is only available as a hosted API. Both answer choice, score, noul and classify questions. Only strom answers route. strom reads up to 32K tokens of state, against 512 tokens for open-jev-deberta-v3-large. open-jev-deberta-v3-large is licensed apache-2.0; strom, proprietary.
Which is more accurate, open-jev-deberta-v3-large or strom?
They report on different suites — open-jev-deberta-v3-large 85.4% on Kotoba held-out test, seen question types (banking77, SST-5, BoolQ), 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, open-jev-deberta-v3-large or strom?
open-jev-deberta-v3-large: Free (open weights). strom: $0.042 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Which is faster, open-jev-deberta-v3-large or strom?
By their publishers’ figures, open-jev-deberta-v3-large answers in about 28 ms at the median and strom in about 136 ms — measured on different hardware, so treat it as a rough guide.
Can I run open-jev-deberta-v3-large or strom locally?
open-jev-deberta-v3-large yes — systemone pull kotoba-labs/open-jev-deberta-v3-large downloads its weights. The other is only served as a hosted API.
Kotoba held-out test, seen question types (banking77, SST-5, BoolQ)
JevBench public set (231 items), the maker's production run of Strom 1.0.7 on 1 Oct 2026 (Open-Jev harness format)
