FrontiersMind's decision model on a base it pre-trained from scratch. Each question reads the state and its own tokens once and a 256-dimension pointer head scores the options; Choice and Score take up to 255 entries, and nothing is generated.
A 149.6M ModernBERT-base cross-encoder with a scalar head that picks an agent's next action or tool from labels and descriptions you supply. Each option is scored against the state and a softmax ranks the set; no text is generated. Experimental preview, not calibrated.
Decides
choice, score, noul
choice, rank, route
Architecture
lumma-fev
modernjev
Fine-tuned from
frontiersmind/lumma-0.6b-base
answerdotai/modernbert-base
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
64.0%
73.4%
Calibration error
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Valid action rate
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Median latency
45.8 ms
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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 lumma-fev and modernjev-decide?
lumma-fev is from FrontiersMind and modernjev-decide from Maziyar Panahi. Both have open weights you can download and run. Both answer choice questions. Only lumma-fev answers score and noul. Only modernjev-decide answers rank and route. lumma-fev reads up to 8K tokens of state, against 4K tokens for modernjev-decide. modernjev-decide is the smaller model, at 150M parameters to 649M.
Which is more accurate, lumma-fev or modernjev-decide?
They report on different suites — lumma-fev 64.0% on typed-decisions (maker's table; split not stated), modernjev-decide 73.4% on AgentToolDecisions-180K held-out test, next action type (1,158 decisions, 3 choices; the maker's split) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, lumma-fev or modernjev-decide?
lumma-fev: Free (open weights). modernjev-decide: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run lumma-fev or modernjev-decide locally?
Yes, both: systemone pull frontiersmind/lumma-fev and systemone pull maziyar-panahi/modernjev-decide download the weights.
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Evaluation suite
typed-decisions (maker's table; split not stated)
AgentToolDecisions-180K held-out test, next action type (1,158 decisions, 3 choices; the maker's split)
