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Run Laya anywhere

Laya Runtimes & Local Deployment

Choose the runtime that matches your language stack, hardware, memory budget, and serving model. These pages track both upstream and community implementations.

Upstream

Laya Python / PyTorch

The upstream reference implementation and Router. Start here for the canonical API, model checkpoints, fine-tuning, and cross-platform inference.

Reference behaviorPython servicesCUDA / CPU
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Community runtime

Laya MLX for Apple Silicon

Community-native MLX runtime for fast local typed decisions on M-series Macs without PyTorch.

Apple SiliconLocal inferenceLow latency
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Community runtime

Laya Node.js / TypeScript via ONNX

Run Laya from Node.js and TypeScript using ONNX Runtime, with the same typed-decision request and response shape.

Node.js backendsTypeScriptONNX Runtime
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Community runtime

Laya MPS on macOS

A memory-conscious local runtime and HTTP server for Apple GPU / MPS, with multiple memory modes and benchmark tooling.

macOSApple GPU / MPSHTTP serving
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Serving layer

Laya Local Serving with Arbiter

Serve Laya behind a Jev-compatible HTTP API with checkpoint routing, batching, metrics, a Playground, and NVIDIA / Apple Silicon recipes.

Local APIJev-compatible clientsNVIDIA GPU
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Independent community resource. Not affiliated with ConvAI Innovations. Laya names and related marks belong to their respective owners.