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.
Together AI's Jev-style classifier. A LoRA fine-tune of Qwen3.5-4B that reads a state, a question and 2 to 24 options and returns one option letter. Served on Together's platform; recipe published.
Decides
choice, score, noul, classify, route
choice, classify, route
Architecture
rune
tev
Fine-tuned from
google/gemma-4-26b-a4b-it
qwen/qwen3.5-4b
License
apache-2.0
Unspecified — weights licence being finalised
Availability
Open weights + hosted API
Open weights + hosted API
Hosted by
Invergent
Together AI
Input price
—
$0.042/MTok
Decision accuracy
—
88.0%
Calibration error
—
—
Valid action rate
—
—
Median latency
—
—
p95 latency
—
—
Evaluation suite
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 rune and tev1?
rune is from Surogate (Invergent) and tev1 from Together AI. Both have open weights and a hosted API. Both answer choice, classify and route questions. Only rune answers score and noul. tev1 is the smaller model, at 4.0B parameters to 26B. rune is licensed apache-2.0; tev1, other.
Which is more accurate, rune or tev1?
Only tev1 publishes an accuracy figure (88.0% on Together development set (reused, not held out)); rune does not, so there is no comparison to make without your own test.
Which is cheaper, rune or tev1?
rune: Hosted, price not published, or free to self-host. tev1: $0.042 / $0 per 1M, or free to self-host. Open weights cost nothing per call beyond your own hardware.
Can I run rune or tev1 locally?
Yes, both: systemone pull surogate/rune and systemone pull together-ai/tev1 download the weights.
