TypeSafe launched Jev recently and I'd been paying for it. It does one thing: text plus a typed question schema in, calibrated probabilities over your options out. No generation, no JSON parsing, no retries. I wanted it on my own GPU. Probed the API for a few days, worked out the design, rebuilt it open. The graph is everything I measured. How it works. State encoded once as a shared prefix, every option appended behind a marker token, block-diagonal mask so question blocks can't see each other, grouped softmax per question. Ten questions about one document cost one forward pass, not ten. I tested the mask rather than trusting it, because a wrong one fails silently. Ten sibling questions that explicitly assert the target's answer move its probabilities by 0.0022 MAD against a 0.0029 noise floor. One question can't prompt-inject another. Jev wins zero-shot, on all seven held-out schemas. 38.3x chance against my 29.6x; 0.938 vs 0.702 on CLINC-150's 151-way menu. I didn't close that gap. Jev's per-item predictions are in the repo so you can check the comparison without an API key. Mine wins for tasks that have labels (finetune). 395 examples, 258 seconds on one H100, an 87 MB adapter: intent 0.979 vs Jev's 0.941, multi-label exact set 0.909 vs 0.822, three wins and four ties on paired McNemar. That comparison is asymmetric and in my favour, since I'm fine-tuned and Jev isn't. The claim is that a few hundred labels beat the gap, not that the models are equal. Serving isn't close. 6,546 decisions/sec on one GPU at 24 ms p50, against Jev's ~47 req/s peak. No HTTP layer in mine, so that's what the hardware does, not a deployment number. Links Technical report (37 pages): https://github.com/S1LV3RJ1NX/openjev/blob/main/report/main.pdf Code: https://github.com/S1LV3RJ1NX/openjev Weights: https://huggingface.co/s1lv3rj1nx/openjev-general-lora Consumer GPU, full-precision probabilities rather than a 0.01 grid, deterministic (Jev isn't, and offers no seed), data never leaves your network.   submitted by   /u/s1lv3rj1nx [link]   [comments]