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-jev-arena
dante01yoon
Compares local Laya and hosted Jev models in games and measurement tools
chinese-workflow-decision-bench
Adkid-Zephyr
Benchmarks Jev and Laya on synthetic Feishu message classification scenarios
stuntdouble
ReallyArtificial
Proxies Jev requests to local decision models and compares their answers on recorded traffic
laya-micro
osamabinIaggin
Prunes and quantizes Laya for low-memory single-board computer deployment
laya-invaders
inhabitants
Uses Laya to choose targets in a Space Invaders game and compares it with a rule baseline
jev-laya-benchmark
EnesDemir143
Benchmarks TypeSafe Jev and Laya-MLX on structured issue classification
laya-learning-demo
Daryl9441
A runnable tutorial teaches Laya decision primitives, routing, fine-tuning, and comparison with Jev
layaAsRagJudge
vishalmysore
Verifies RAG claims in the browser using Laya decisions and evaluates accuracy against labeled claims
laya-cuda
adamjen
Benchmarks Laya typed-decision checkpoints with a CUDA backend on NVIDIA GPUs
laya-exp
changtimwu
Experiments comparing an MLX Laya port with Jev and a TypeSafe-compatible Laya client
laya-lab
Alevsk
Runs Laya locally with reproducible scenarios that explore its capabilities on Apple Silicon
laya-inference-engine
aaditagrawal
Provides a GPU inference engine and performance modes for Laya on NVIDIA Blackwell
verdict
Manavarya09
Provides calibrated zero-shot and fine-tuned typed decision models as an alternative to Jev
laya-vs-dijkstra
antonellof
Compares Laya MLX pathfinding decisions with Dijkstra on seeded weighted mazes
Laya-Finetune
zamax14
Fine-tunes and evaluates multilingual Laya for support-ticket classification
cbjev
tomek7667
Implements a Jev-compatible decision model and benchmarks it directly against Laya
apm-laya-triage
danielmeppiel
Benchmarks local Laya issue classification against labels in the Microsoft APM corpus
laya-calibration-lab
BunsDev
Fits and evaluates probability calibration for Laya typed-decision models
laya-system1-snake
Kamandlou
A terminal Snake game uses Laya MLX to choose moves from structured game-state features
laya-eval
yliuai
Fine-tunes Laya to play Snake on a Mac and measures base vs fine-tuned decision accuracy
chong-laya
cloudwallker
Provides a local interface for inspecting Laya shopping decisions, probabilities, latency, and raw responses
jev_laya_studies
professortavares
Explores structured text decisions, explainability, and comparisons involving Jev and Laya
system-one-web-ai
Josuesp1620
An interactive web guide measuring Laya on Spanish customer-service messages and explaining its implementation
laya-persian-benchmark
alipyth
Benchmarks Laya's Persian support-triage decisions across eight language-specific message families
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