Global

Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.

8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. cpp and MLX.

Qwen3-8B on a real BANKING77 item. Every number is a model output.

Jev-like family of decision models built on top of Qwen3.5/3.8 you can train and run on your own

The GIF is an original-speed render of a real local Snake run. Every move calls Laya; the visible cycle safety layer can correct unsafe proposals. The latency figures above are the separate one-question API benchmark, not the frame time of the three-question Snake loop.

This release contains training, two inference backends, benchmark scoring, temperature calibration, and a browser demo.

Language models are extraordinary at understanding intent. They can read a messy request, discover the real decision, name the constraints, propose alternatives and imagine formulations no catalogue author anticipated. But imagination is not execution.

Gaussian blur reveals how Valen-Preview-0923 adapts its decisions and confidence as visual detail decreases. 2% at the strongest blur.

jevos: an open-source alternative to Jev and Microsoft-Decision-1. Yes/no decisions, choices and scores with probabilities, on your laptop's CPU.

Strands decider is one of a new class of decision models, or "system one" models. Unlike an LLM, which can generate arbitrary text, a decision model picks between sets of options and rates things on a scale.

Structured multi-perspective deliberation for hard decisions. Run full councils, focused triads, or duo debates across Claude Code, Codex, Gemini CLI, and OpenCode.

> New project: JevHarness — Let an LLM build task-specific decision harnesses with Jev, with optional refinement using rewards and execution traces. Includes an interactive Pokémon demo.

Give it a ticket, specification, bug report, or any free-form software job.

> Not financial advice. beebots is an experiment and a piece of open-source software. It is not a trading product, > and nothing it does is a recommendation to buy or sell anything.

> Beta. This is under heavy development. x releases.

Awesome Jev: source-backed open-source ecosystem radar, plain-language project discovery, and automatic GitHub sync

The System One harness for System One models. ai.

Local Laya typed decisions on Apple Core ML and Neural Engine. Validated ports, 5 ms short decisions on M3 Max, reproducible speed and energy benchmarks.

The job · Primitives · Forward pass · Results · Latency · Run it · HTTP · Repository

🎮 Results & Demos | ⚡ Quickstart | 💻 Run locally | 🤗 Models | 📊 Benchmarks | 📚 Docs

非自回归System 1决策引擎，专为结构化类型决策场景设计 DeepOpen Multilingual, non-autoregressive System 1 decision engine.

A Jev-like model takes a piece of text and a list of N text options. It returns one probability for each option. It does this in one pass instead of writing an answer word by word.

The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.

Turns a vague request into a typed IntentSpec: it looks up what it can, asks only what it can't, calls out a request that contradicts itself, admits two readings, or rests on a premise your own repo already disproves, and refuses to emit while the intent is still underspecified.

1207 public resources for Jev, TypeSafe AI's System One decision model, indexed by decision pattern. Source citations, dated link checks and scheduled call-site text checks; runtime and performance are not independently tested here. EN/中文, JSON schema and platform compatibility.

\ No Kev-9B JevBench result is published. These are Kev-8B (Qwen3).