Laya vs Jev
Run typed decisions on your own machine, or call hosted System One in the cloud. Same kind of question, very different homework.
Laya is Convai's open-weight family of decision models. You ask Choice, Score, or Noul questions over structured state. One forward pass, no chat essay. TypeSafe Jev is the hosted System One API many teams already plug into agents, gateways, and moderation pipelines.
Both help software make judgment calls. They differ in who hosts the GPU, what you can download, and how you pay. fyi. We are not TypeSafe or Convai. We link primary sources and say plainly when a vendor benchmark is not an independent audit.
Guides in this series
Laya vs Jev: open weights or a hosted API
Same typed primitives, different deployment. Read this before you rip out a working Jev integration on a Friday afternoon.
Read guide →What is Laya?
Convai's open decision family: one forward pass, Choice / Score / Noul, Apache 2.0. Not a tiny chatbot wearing a trench coat.
Read guide →Laya-MLX on Apple Silicon
Community MLX runtime for local Laya inference. Fast short decisions on a Mac. Not an official Convai build.
Read guide →Benchmarks and fairness
How to read Convai's Laya vs Jev tables and laptop MLX numbers without fooling yourself (or your CFO).
Read guide →Migration and coexistence
Map Jev-shaped gates to Laya checkpoints without breaking production. And know when not to migrate.
Read guide →Privacy, air-gap, and agents
When local Laya belongs in the agent loop. And how that differs from bolting Jev MCP tools onto a chat model.
Read guide →
Fair comparison reminder
Local GPU or MLX milliseconds are not the same metric as hosted Jev end-to-end latency. Vendor-published Laya-vs-Jev accuracy tables mix benchmarks and are not independent third-party audits. Laya is not a drop-in replacement for Jev context limits, ops, or default option budgets. Readbenchmarks and fairnessbefore you quote numbers in a pitch deck.
FAQ
- Is Laya a drop-in replacement for Jev?
- No. APIs, context limits, option budgets, calibration, and ops all differ. Laya gives you checkpoints to host. Jev is a managed POST /v1/systemone service with gateway integrations. Many teams run Laya locally for fast gates and Jev where they want hosted scale. See migration-and-coexistence.
- Jev vs Laya: which should you use?
- Pick Laya when you need open weights, on-prem or edge inference, and you can run GPUs. Pick hosted Jev when you want a supported API, gateway billing, and large option sets without tuning head budgets yourself. Hybrid stacks are common. Start with the comparison overview in this hub.
- Who makes Laya and who makes Jev?
- Laya weights and the upstream Python SDK come from Convai Innovations (Apache 2.0 on Hugging Face). Laya-MLX is a community MLX port for Apple Silicon, not an official Convai release. Jev is TypeSafe's commercial System One product. This directory curates the ecosystem but does not speak for TypeSafe.
- Can I trust latency numbers in blog posts?
- Treat them as hints, not promises. Local GPU milliseconds (Laya on T4 or M3 Max) are not the same as end-to-end hosted API latency (network, auth, batching, region). Convai's Hugging Face card cites third-party Jev p50 figures (about 236-276 ms) next to their own Laya GPU times (about 33 ms on T4). Those are different measurement setups. Read benchmarks-and-fairness before you put numbers in an SLA.
- Where is the snake demo with Laya-MLX?
- The showcase embeds Lonely__MH's laya-mlx snake clip on Apple Silicon: /showcase?demo=laya-mlx-lonely-mh. It shows a local decision loop. It is not a benchmark certificate.
- Does this site host Laya weights?
- No. We link Hugging Face, GitHub, and PyPI. Download and license compliance stay on your side.