An open family of System One models. A LoRA adapter plus a pointer head on a frozen Qwen base returns a distribution per typed question in one forward pass, serves TypeSafe's /v1/systemone contract, and ships a fitted temperature with every checkpoint.
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
kev
tev
Fine-tuned from
qwen/qwen3.5-4b-base
qwen/qwen3.5-4b
License
apache-2.0
Unspecified — weights licence being finalised
Availability
Open weights
Open weights + hosted API
Hosted by
—
Together AI
Input price
—
$0.042/MTok
Decision accuracy
83.8%
88.0%
Calibration error
0.042
—
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 kev and tev1?
kev is from Jared Palmer and tev1 from Together AI. kev has open weights you can download and run; tev1 has open weights and a hosted API. Both answer choice, classify and route questions. Only kev answers score and noul. kev is licensed apache-2.0; tev1, other.
Which is more accurate, kev or tev1?
They report on different suites — kev 83.8% on transfer-v4 (locked, out of domain), tev1 88.0% on Together development set (reused, not held out) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, kev or tev1?
kev: Free (open weights). tev1: $0.042 / $0 per 1M, or free to self-host. Open weights cost nothing per call beyond your own hardware.
Can I run kev or tev1 locally?
Yes, both: systemone pull jared-palmer/kev and systemone pull together-ai/tev1 download the weights.
