The flagship of the vLLM Semantic Router team's Decision 1.0 family. Qwen3.5-9B with a shared candidate head returns a probability for every supplied answer to choice, yes/no and score questions, over a 16,384-token input.
AutoTrust's student of TypeSafe Jev 1.13. A frozen Qwen3.8-27B plus a 108.9M-parameter decision block trained on Jev's own output distributions; one set of weights answers typed questions in one pass (System 1) or generates text with the untouched base (System 2).
Decides
choice, score, noul, classify, route
choice, score, noul
Architecture
decision
blocks-of-experts
Fine-tuned from
qwen/qwen3.5-9b
qwen/qwen3.8-27b
License
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
77.4%
88.7%
Calibration error
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Valid action rate
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Median latency
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137 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 decision and jev-27b?
decision is from vLLM Semantic Router and jev-27b from AutoTrust AI Lab. Both have open weights you can download and run. Both answer choice, score and noul questions. Only decision answers classify and route. decision is the smaller model, at 9.0B parameters to 27B.
Which is more accurate, decision or jev-27b?
They report on different suites — decision 77.4% on vLLM-SR decision benchmark (54 tasks, 3,766 decisions, weighted), jev-27b 88.7% on JevBench public set (231 items), family-macro score, maker's run — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, decision or jev-27b?
decision: Free (open weights). jev-27b: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run decision or jev-27b locally?
Yes, both: systemone pull vllm-semantic-router/decision and systemone pull autotrust-ai/jev-27b download the weights.
