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.
Upstage's structured decision model, a System One endpoint on Solar Mini 4. Returns a choice, a score or a yes/no answer with a probability read from the model, in one forward pass, on the same /v1/systemone schema as Jev.
Decides
choice, score, noul
choice, score, noul, classify, route
Architecture
lumma-fev
solar
Fine-tuned from
frontiersmind/lumma-0.6b-base
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License
apache-2.0
proprietary
Availability
Open weights
Hosted API
Hosted by
—
Upstage
Input price
—
$0.10/MTok
Decision accuracy
64.0%
—
Calibration error
—
—
Valid action rate
—
—
Median latency
45.8 ms
—
p95 latency
—
—
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 solar-decide?
lumma-fev is from FrontiersMind and solar-decide from Upstage. lumma-fev has open weights you can download and run; solar-decide is only available as a hosted API. Both answer choice, score and noul questions. Only solar-decide answers classify and route. solar-decide reads up to 512K tokens of state, against 8K tokens for lumma-fev. lumma-fev is licensed apache-2.0; solar-decide, proprietary.
Which is more accurate, lumma-fev or solar-decide?
Only lumma-fev publishes an accuracy figure (64.0% on typed-decisions (maker's table; split not stated)); solar-decide does not, so there is no comparison to make without your own test.
Which is cheaper, lumma-fev or solar-decide?
lumma-fev: Free (open weights). solar-decide: $0.1 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Can I run lumma-fev or solar-decide locally?
lumma-fev yes — systemone pull frontiersmind/lumma-fev downloads its weights. The other is only served as a hosted API.
