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).
Metask Lab's calibrated decision model in 16 languages. Qwen3.5-4B with a merged LoRA trained with the Nimble candidate-logit objective; one forward pass and a softmax over at most 26 answer-letter logits, with one temperature per question type.
Decides
choice, score, noul
choice, score, noul, classify, route
Architecture
blocks-of-experts
metask-jev
Fine-tuned from
qwen/qwen3.8-27b
qwen/qwen3.5-4b
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
88.7%
80.1%
Calibration error
—
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Valid action rate
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Median latency
137 ms
62.8 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 jev-27b and metask-jev?
jev-27b is from AutoTrust AI Lab and metask-jev from Metask Lab. Both have open weights you can download and run. Both answer choice, score and noul questions. Only metask-jev answers classify and route. metask-jev is the smaller model, at 4.5B parameters to 27B.
Which is more accurate, jev-27b or metask-jev?
They report on different suites — jev-27b 88.7% on JevBench public set (231 items), family-macro score, maker's run, metask-jev 80.1% on JevBench v1.2 public set (231 items) at 4,096 tokens, maker's run — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, jev-27b or metask-jev?
jev-27b: Free (open weights). metask-jev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, jev-27b or metask-jev?
By their publishers’ figures, metask-jev answers in about 62.8 ms at the median and jev-27b in about 137 ms — measured on different hardware, so treat it as a rough guide.
Can I run jev-27b or metask-jev locally?
Yes, both: systemone pull autotrust-ai/jev-27b and systemone pull metask-lab/metask-jev download the weights.
Evaluation suite
JevBench public set (231 items), family-macro score, maker's run
JevBench v1.2 public set (231 items) at 4,096 tokens, maker's run
