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.
Invergent's decision model for text and images. A fine-tune of Gemma-4-26B-A4B (about 4B parameters active per token) that answers Choice, Noul and Score questions, with an optional thinking mode for harder questions.
Decides
choice, score, noul
choice, score, noul, classify, route
Architecture
lumma-fev
rune
Fine-tuned from
frontiersmind/lumma-0.6b-base
google/gemma-4-26b-a4b-it
License
apache-2.0
apache-2.0
Availability
Open weights
Open weights + hosted API
Hosted by
—
Invergent
Input price
—
—
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 rune?
lumma-fev is from FrontiersMind and rune from Surogate (Invergent). lumma-fev has open weights you can download and run; rune has open weights and a hosted API. Both answer choice, score and noul questions. Only rune answers classify and route. rune reads up to 262K tokens of state, against 8K tokens for lumma-fev. lumma-fev is the smaller model, at 649M parameters to 26B.
Which is more accurate, lumma-fev or rune?
Only lumma-fev publishes an accuracy figure (64.0% on typed-decisions (maker's table; split not stated)); rune does not, so there is no comparison to make without your own test.
Which is cheaper, lumma-fev or rune?
lumma-fev: Free (open weights). rune: Hosted, price not published, or free to self-host. Open weights cost nothing per call beyond your own hardware.
Can I run lumma-fev or rune locally?
Yes, both: systemone pull frontiersmind/lumma-fev and systemone pull surogate/rune download the weights.
