Laya on MLX
laya-mlx is an independent MLX port of Laya that runs the original weights on the Apple Silicon GPU with no PyTorch or Transformers runtime. It keeps upstream prompt formatting, calibration and output schema, and it is the base for many Mac demos, agents and benchmarks.
260 projects
laya-mlx-windows-cuda
oboroge0
Documents running the MLX Laya model on Windows with an NVIDIA GPU
jev-systemone-local
katya4oyu
Plans a local Jev-compatible System One server with MLX, Core ML, and ONNX Laya backends
SEO-Agent-using-LAYA
07anishu12
Audits websites and uses Laya MLX inference to classify and prioritize SEO issues
MacJev-322M-4K-Laya
lawrence3699
Provides a fine-tuned Laya-derived decision model for local Mac agents
Autonomous-Decision-Intelligence-Platform-ADIP-
Ayyankhan101
Blueprints a local Laya-based decision platform using the laya-mlx runtime
MacJev-322M-4K-Laya-MLX
lawrence3699
Runs the MacJev typed-decision model natively on Apple silicon with MLX and compares it with Laya
stf-sim
JonRoosevelt
Simulates Brazilian Supreme Court cases using local Laya decisions, retrieval and bias probes
identity-jev
clawdreyhepburn
Fine-tunes Laya to rank identity and authentication standards from plain-language queries
zhiyan
liuqing0224
Provides macOS chat assistance with local Laya analysis and generated reply suggestions
Verdict
TobyNoSkillSon
Keeps local System One models, including Laya, ready for coding-agent classification and scoring
jev-context-rot
casperkwok
Reproduces an experiment comparing context sensitivity in Jev, Laya and Decider models
LayaService
wj1313677
Serves the Laya decision model through a local REST API using MLX on Apple Silicon
classifier-laya
josecruset
A local browser interface for testing Laya-MLX typed-decision models on Apple Silicon
jev-vs-laya
Cognition-Forge
Compares Jev and Laya variants across typed-decision tasks
laya-universal
abusuraihsakhri
Provides cross-platform inference utilities for Laya checkpoints using ONNX Runtime and MLX
laya-101
alejandro-torrero
A minimal starter that runs Laya on a Mac with laya-mlx
laya-vs-jev
alilibx
Benchmarks open-weight Laya models against TypeSafe Jev on labelled datasets
laya-mlx-voxel
yuxino
Builds voxel reliefs by using Laya-MLX to choose extrusion depths from image pixel statistics
dino-jump
ozbillwang
A browser runner game uses Laya scores to evaluate jump, duck, and run actions
TetrisGame_Laya
RehmanaliMomin
Plays Tetris by using a fine-tuned Laya model to choose piece rotations and drop columns
laya-local-http-server
ratheesh-aot
Serves the Laya typed-decision model through a local HTTP API using MLX or PyTorch
laya-vs-jev-traffic
ameeetgaikwad
Compares local Laya and cloud Jev in a real-time traffic-control simulation
laya-fine-tune-bn-eco-voice
nafi-ullah
Fine-tunes multilingual Laya for typed decisions in a Bangla e-commerce voice agent
nlaut
benkya
Runs natural-language browser tests with deterministic, vision-model, and Laya-based judgments
Install
Requirements from the laya-mlx README: Apple Silicon, Python 3.11+, macOS 14+.
pip install laya-mlx
Pre-converted FP16 checkpoints are on Hugging Face: aac6fef/laya-mlx, aac6fef/laya-multilingual-mlx and aac6fef/laya-typed-decisions-mlx. You can also load the original convaiinnovations/laya IDs.
Router and CLI
The port includes the upstream language router and presets:
from laya_mlx import Router, triage_questions
router = Router(dtype="float16", max_loaded=2)
result = router.predict({"message": "发票被重复扣款，请退款。"}, triage_questions())
print(result["routing"]) # multilingual
For the terminal demo, where Laya plays Snake:
pip install 'laya-mlx[demo]'
hf download aac6fef/laya-multilingual-mlx
laya-snake
Reported numbers
On an M3 Max, FP16, one short question: 13.42 ms P50 for the 421M English model and 7.39 ms for the 322M multilingual model. The README states that all three checkpoints matched the upstream answer on 63/63 validation questions in FP32 and FP16. That measures port fidelity, not task accuracy.
Projects built on laya-mlx
- laya-ultrafast: a port of browser-use/jev-ultrafast that makes browser decisions locally.
- laya-mcp (wsargent): an MCP server with triage, guard, moderation and email tools.
- laya-fast: adds Neural Engine execution next to the MLX GPU.
- laya-jev-lab and jev-laya-benchmark: independent Jev comparisons that use laya-mlx as the Laya side.
- laya-vs-jev: Laya and Jev playing Chrome's T-Rex game side by side.
Caveats
This is not an official Convai Innovations release. Training and fine-tuning stay in the upstream project. BF16 can be requested but is not part of the published validation.
More ways to use Laya