lev
An open System One model from Interfaze AI. A rank-32 LoRA on Qwen3.5-4B reads yes/no, choice and score answers from the logits of one forward pass, returns calibrated probabilities and serves the /v1/systemone API.
On all 13 S1Bench subsets (Bespoke's public manifests) lev scores 68.9% macro against 76.1% for Jev in the same harness, with a mean calibration error of 0.115 (Jev 0.091). On a held-out split of its 29 training sources it reaches 80.7% (calibration error 0.061), 98.0% on banking77 and 96.8% on clinc_oos. Engine compute is 69 ms on an H100 for a short request. Choice sets above 68 options move to a candidate-path head, so there is no fixed option limit. English only. The adapter is Apache-2.0, but some of its training datasets carry non-commercial terms; check them before commercial use.
What it decides
- choice — picks one option from a set
- score — places the input on an ordered scale
- noul — answers a yes/no question with one calibrated probability
- classify — assigns a category from a fixed taxonomy
- route — sends the input to one of several destinations
At a glance
| Parameters | 4B |
| Base model | qwen/qwen3.5-4b |
| Maker | Interfaze AI |
| Released | 2026-09-24 |
| License | apache-2.0 |
| Reported accuracy | 68.9% |
| Reported latency | 69 ms engine compute on an H100 (short request); 414–654 ms end to end on Modal |
Get the weights
pip install systemonemodels
systemone pull interfaze-ai/lev
The files are served from the maker's Hugging Face repository, interfaze-ai/lev, and verified against the checksums recorded here.
Read more
This page was opened by System One for Interfaze AI, who can claim the organisation and take it over at any time.