Laya vs Jev
You found Laya — the open-weight decision model — and now you want to know how it stacks up against Jev, the hosted original. Both answer typed questions instead of writing text; the split is open-and-local versus hosted-and-calibrated. Here's the honest comparison, including what Laya's own benchmark claims do and don't prove.
Laya (Convai Innovations) shipped open weights under Apache 2.0 a few days after TypeSafe launched Jev, and it targets the exact same job: a state and typed questions in, a decision with a probability distribution out — no free text. The difference is ownership. Jev keeps the model hosted and calibrated; Laya hands you the weights to run, fine-tune and pin yourself.
Laya vs Jev at a glance
| Laya (open) | Jev (TypeSafe) | |
|---|---|---|
| What it is | Open-weight System One model | Hosted System One API |
| Weights | Open (Apache 2.0) | Closed, versioned & pinned |
| Runs | Local — MLX (Mac), ONNX (Node), GPU | Hosted — just a key |
| Calibration | Your responsibility; validate it | RLCD-trained, calibrated |
| Latency (reported) | ~33 ms (model card); ~7–14 ms MLX in-process | ~70–500 ms incl. network |
| Cost | Free to run; you pay compute | ~$0.001 / decision, output free |
| Setup | Install weights + runtime | Minutes — grab a key |
| Best for | Privacy, offline, fine-tuning, volume | Production, no ops, trusted numbers |
About Laya's benchmark claims
Laya's model card claims it beats Jev — figures like ~83.8% vs 67.8% accuracy and ~33 ms vs ~236–276 ms latency circulate widely. Read them as vendor-reported on Laya's own benchmark, not a neutral head-to-head. Community game demos that reward low latency flatter fast local models, and calibration — whether a stated 0.8 is right ~80% of the time — is exactly what an open checkpoint doesn't guarantee. The honest takeaway: Laya is impressively fast and clearly capable, but validate accuracy and calibration on your own labelled data before you trust a claim.
When Laya wins
Choose Laya when control and economics dominate: the decision must stay on your hardware (regulated data, offline), you want to fine-tune on your domain, or you're running such high volume that per-call pricing hurts. Its MLX build runs in-process on a Mac with no server and no bill, which is genuinely hard to beat for local dev and privacy.
When Jev wins
Choose Jev when you want a calibrated number you can threshold and forget. Because the weights are pinned and RLCD-trained, a rule like "escalate if p > 0.8" keeps meaning the same thing between deploys instead of drifting, and you carry no GPUs, no weight updates, no calibration validation. For production decisions where a wrong-but-confident answer is expensive, that reliability is the whole point.
Run both — or try each
Many teams will pair them: Laya for local, private, high-volume bulk work and Jev for the calls that need a pinned, calibrated contract. Both speak the same primitives, so your interface stays the same while you swap the backend. Want to deploy Laya? The step-by-step is on the Laya local guide. Want to feel the hosted side? The playground runs a real calibrated decision in the browser, free.
FAQ
Is Laya better than Jev?
Laya's own model card claims higher accuracy and much lower latency, but those are vendor-reported on its own benchmark. Laya is faster and open; Jev is hosted and calibrated. Which is 'better' depends on whether you value local control and speed or a pinned, trusted-calibration contract — validate on your own data before deciding.
Is Laya free and Jev paid?
Laya's weights are free to download and run under Apache 2.0 (you pay your own compute). Jev is a hosted API billed at about $0.001 per decision, output free. Free-to-run doesn't mean free — you take on GPUs, ops and calibration work with Laya.
Can I self-host Laya as a Jev replacement?
Yes for many cases — Laya runs locally via MLX (Mac), ONNX (Node) or on a GPU, and speaks the same typed-decision shape. You take on calibration and quality validation in exchange for open weights and no per-call cost. See the Laya local deploy guide.
Which is faster, Laya or Jev?
Laya, on paper: its model card reports ~33 ms and community MLX builds run in ~7–14 ms in-process, versus Jev's ~70–500 ms including the network hop. Real latency depends on your hardware — benchmark it.
See also: Deploy Laya locally (guide) · Jev vs Laya (hosted-first view) · NanoJev vs Jev · Playground
Try the hosted, calibrated side free
Before you commit to self-hosting Laya, run a real calibrated decision in the browser — no signup — then grab a jv_live_ key if hosted fits.