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.
Respan's behaviour-scoring model for evals, guardrails and monitoring. For each plain-language behaviour you define, it reads a conversation or agent trace and returns the probability the behaviour is present, absent or not observable, in one forward pass.
Decides
choice, score, noul
noul, classify
Architecture
lumma-fev
span
Fine-tuned from
frontiersmind/lumma-0.6b-base
—
License
apache-2.0
proprietary
Availability
Open weights
Hosted API
Hosted by
—
Respan
Input price
—
$0.020/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 span-01?
lumma-fev is from FrontiersMind and span-01 from Respan. lumma-fev has open weights you can download and run; span-01 is only available as a hosted API. Both answer noul questions. Only lumma-fev answers choice and score. Only span-01 answers classify. lumma-fev is licensed apache-2.0; span-01, proprietary.
Which is more accurate, lumma-fev or span-01?
Only lumma-fev publishes an accuracy figure (64.0% on typed-decisions (maker's table; split not stated)); span-01 does not, so there is no comparison to make without your own test.
Which is cheaper, lumma-fev or span-01?
lumma-fev: Free (open weights). span-01: $0.02 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Can I run lumma-fev or span-01 locally?
lumma-fev yes — systemone pull frontiersmind/lumma-fev downloads its weights. The other is only served as a hosted API.
