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-experiments

Mac-007

Runs experiments and empirical evaluations of Laya for text-based decision making

0·GitHub repo

laya-trader

zakanysa

Tests Laya-driven trading strategies on an on-chain order book and evaluates their real costs

0·GitHub repo

laya-benchmark

LokenSI

Benchmarks local decision models and Jev against Laya on English and Norwegian tasks

0·GitHub repo

laya_mobile

SerAbin1

A Flutter app for testing Laya model performance on mobile

0·GitHub repo

laya-fast-finetune

sathwikbs

Fine-tunes Laya with a packed training layout to reduce repeated state encoding

0·GitHub repo

Jev-OpenSource-Alternative-Laya

Nagwa-Ahmed

Evaluates local Laya checkpoints on zero-shot text classification datasets and exports Excel reports

0·GitHub repo

agent-failure-triage

PawnsApprentice

An experiment compares Laya with TF-IDF and an LLM judge for triaging failed agent runs

0·GitHub repo

compare-IA-decision

laurentvv

A benchmark harness compares local System One decision models, including Laya, using measured results

0·GitHub repo

Jev-OpenSource-Alternative-DEMO-Laya

Nagwa-Ahmed

Evaluates local Laya classification across Hugging Face datasets and exports Excel reports

0·GitHub repo

aubin

Emrevrg

Provides calibrated decision models, computer-use tools, and a Laya/Jev-compatible API

0·GitHub repo

layaFineTuning

codingpipeline

Fine-tunes Laya to route customer return requests and evaluates its accuracy and safety

0·GitHub repo

the-new-turing-test

glowleaf

A Magic: The Gathering game harness tests Laya as a player

0·GitHub repo

laya-banking77

hari-hashing

Evaluates Laya decision-model classification and routing on the Banking77 intent dataset

0·GitHub repo

laya-bias-audit

maheshwari2000

An audit measures option-order, key, and wording biases in Laya decision-model checkpoints

0·GitHub repo

HeXA-laya-demo

queso-gato1355

A local dashboard demonstrates Laya decisions for an autonomous delivery robot scenario

0·GitHub repo

hybrid-decision-agent

musaugurlu

Tests a Laya-first agent architecture that routes requests to Gemini Flash and benchmarks its performance

0·GitHub repo

Laya_Jev_opensource_guide

gotree94

Explains how to self-host Laya and Jev, including setup, fine-tuning, and benchmarks

0·GitHub repo

laya-vs-jev-toxicity

jmgb27

Compares Jev and fine-tuned Laya on toxicity classification using Civil Comments

0·GitHub repo

distill-public

abhi-sama

Fine-tunes local Laya decision models from synthetic data and evaluates and exports calibrated models

0·GitHub repo

laya-demo

bbaotran

Snake game played by Laya on CPU, with Jev and other decision backends for comparison

0·GitHub repo

jev-laya-lab

KarlPeixoto

Explores Laya and JEV decision-making through Python experiments and evaluations

0·GitHub repo

laya-local-benchmark

saksham-personal

Benchmarks and packages offline CPU Laya decision workflows for Windows VDI environments

0·GitHub repo

Sytem-1-model-testing--jev--Laya-

dinod001

Benchmarks System 1 decision models against autoregressive LLMs for latency, cost, and accuracy

0·GitHub repo

system1-prompt-lab

msmidhunms

Evaluates and compares Laya and other System 1 classifiers with datasets and prompt optimization

0·GitHub repo

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