Laya benchmarks
The official Laya README publishes detailed numbers, and a growing set of independent repositories now test those claims. The overall picture: Laya is much faster when run locally and free to self-host, while Jev is more accurate out of the box on most shared tests.
539 projects
laya.cpp
kyr0
Implements native C++ inference and a JEV-compatible server for Laya typed decisions
laya-minesweeper
Animal2404
Demonstrates and evaluates Laya’s mine-risk judgments against a Minesweeper constraint solver
laya-snapdragon
piffie
Runs Laya typed decisions on Snapdragon X NPUs through ONNX Runtime and Qualcomm QNN
laya-tetris
kuchris
Runs Laya as a Tetris placement decision-maker with a heuristic safety guard
Laya_Playground
jonas050210
Runs local Laya decision demos, games, and a raw playground through a browser interface
laya-burmese
aungthuhein2005
Studies Laya zero-shot transfer, calibration, and fine-tuning for Burmese topic classification
laya-todo
firede
Classifies to-do items locally with Laya and compares its predictions with an optional Kev backend
laya-codex-bench
pbrehmer-ai
Benchmarks Laya-assisted Codex workflows for call reduction, latency, and decision quality
laya-gfx1030
Thotheris
Runs and benchmarks the Laya decision model on Windows with an AMD Radeon RX 6900 XT
laya-hexagon-npu
EricYu123456
Deploys Laya inference on Qualcomm Hexagon NPU using ONNX Runtime
exp-laya-router
zheyar-ltd
Demonstrates a CUDA-based Laya policy router in real-time Snake and Tetris games
laya-capability-business
matrix-air
Presents experiments measuring Laya’s capabilities, limitations, fine-tuning, and runtime migration
laya-vs-jev
darrenli6
Compares Laya and Jev in snake-racing and fighting-game arenas
jev-vs-laya
janagarajsn
A Flask app benchmarks Jev and local Laya on synthetic customer-support tickets
laya-jev-eval
yuvrajrox
Evaluates Laya against Jev on email intent and explores text generation with Laya’s backbone
laya-open-eval
lgy1027
Packages local Laya inference and evaluation with an optional HTTP adapter
laya-vs-llms
Ujjwal3115
Benchmarks Laya against hosted language models on developer commit triage and CI safety decisions
laya-zh-eval
lzero07
Evaluates Laya checkpoints on Chinese skill-routing requests
laya-support-ticket-triage
IshaanLabs
A local Laya system triages customer-support tickets and benchmarks results in an interactive dashboard
laya-or-jev-pong
bananadonn
Compares local Laya and hosted Jev decision APIs by having them control paddles in Pong
llm-jev-laya-bench
PerryLink
Measures the cost, latency, and failure boundaries of judgment layers
laya-gtx1650-benchmark
PredictiveManish
Measures Laya inference latency on a laptop with a GTX 1650 GPU
laya-vs-llm-benchmark
Shray15
Benchmarks Laya against a local LLM for selecting MCP tools
pol2-laya-studio
shentonyan
A local interactive playground visualizes and evaluates typed decisions from Laya models
Official numbers
The core README and its BENCHMARKS.md report latency on a Tesla T4 (32.8 ms for one question with laya-multilingual, 39.5 ms with laya) and accuracy across 51 languages. Its Jev figures are third-party published, not measured by the Laya authors.
Independent head-to-heads
- sysone-bench: byte-identical inputs across 751 states. Jev leads on triage, guardrails, moderation, Banking77 and multilingual intent. Laya leads on AG News and MNLI.
- jev-laya-benchmark: 1,470 synthetic items. Jev 92.9% vs Laya 65.3% of judgments correct. For a single question, Laya was 42 ms locally on an M3 Pro and Jev was 136 ms. Jev was faster above 3 to 4 questions per request.
- laya-jev-lab: 40 Chinese support tickets. Jev 78% at 588 ms, Laya 57% at 7.6 ms on an M4 Max. A cascade that escalates below 0.60 confidence matched Jev's accuracy at 1.8x its speed.
- JevBench: a composite board. In v1.4.2, Laya (English, CPU) ranks 41st with a score of 30.25 and Jev 1.13.0 ranks 2nd with 63.29.
- laya-mcp eval: key accuracy 32.5% for Laya vs 98.8% for Jev, with median latency of 26 ms vs 138 ms.
CPU latency
laya-cpu-benchmark measured laya-multilingual in steady state on an Intel i9-14900HX. One question took 50 ms for a 71-token state, 307 ms for 261 tokens, and 1,315 ms for 927 tokens. Batching gave little gain on CPU. Its conclusion: a realistic CPU call is 0.3 to 2 seconds, not 33 ms.
Run your own
git clone https://github.com/glukicov/laya_router && cd laya_router
uv sync --all-extras
uv run laya-router eval run --backend laya --device mps
Or use jevbench (dhruvmehra) to compare Jev, Laya, LLMs and BERT models on public datasets.
Reading these numbers
Most of these suites are small (40 to 1,500 items), synthetic or in one domain, and their authors say so. Latency depends on hardware, state length and question count. The core README's own advice: treat Laya as a fast base to specialise, and fine-tune for accuracy.
More ways to use Laya