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-2048
DjTaNg-404
Uses local Laya weights to play 2048 with browser, terminal, and batch-testing interfaces
laya-snake-cuda
kuchris
Compares Laya and SemIf for local real-time Snake decisions with a CUDA dashboard
lunar-mpc-laya
mraad
Pairs Laya with adaptive model-predictive control in a lunar lander decision game
laya-mlx-demo
knishika62
Uses laya-mlx to classify Japanese virtual streamer personas and compare results with an LLM
jev-vs-laya
mouadse
Benchmarks hosted Jev, Kev-9B, and Laya on Moroccan Darija sentiment classification
laya-onnx-runtime
zenryokukikai
Ports the Laya multilingual decision model to CPU-only ONNX Runtime
laya-snake-arena
sathwikkuncham
Compares local Laya and Jev decision engines in a configurable Snake arena
jev-laya-chess-bench
abe17124
Compares TypeSafe Jev and Laya in head-to-head chess games using legal moves
jev-laya-japanese-business-benchmark
snsk
Compares Jev and Laya on a Japanese business decision benchmark
decisionmakertest
vittoriobrehautduran
Benchmarks Jev and Laya on typed decisions, labeled cases, and a small dungeon game
ai-decision-lab
uibuckets
Provides a local playground and benchmark harness for Laya, with optional Jev comparisons
IOCArena
hc-nolan
Compares Jev, Von, and Laya decision models on VirusTotal data
jev-zen
loongWoong
Reconstructs and validates Laya inference locally using NumPy and a browser-based interface
jev-eval-ja
unirt
Benchmarks Jev and Laya on Japanese business-style decision tasks
laya
harisathees
Tests Laya predictions, multilingual behavior, CPU performance, and interactive runs through a local web console
product_search_bench
Wanke15
Compares BM25, Jev, Qwen, and Laya for product search and reranking
laya-t-rex-runner
10086ggqq
A browser-based T-Rex runner uses typed-decision models and distilled agents to choose actions
laya-ROCm
don-milsey-miller
Provides an AMD ROCm runtime and benchmarks for running the Laya decision model
laya-vk
sulistta
Ports the Laya decision runtime to a Vulkan/IREE encoder backend for AMD and Qualcomm GPUs
laya-tictactoe
Kasa-Harendra
A terminal Tic-Tac-Toe demo runs the Laya model locally through Core ML on Apple Silicon
laya-onnx
Geoking2104
Runs Laya decision models with ONNX Runtime and provides export, inference, and benchmark tools
laya-agent
adhishthite
Benchmarks ConvAI Laya against TypeSafe Jev with and without live web grounding
laya-example
lim6112j
Demonstrates typed-question routing with Laya checkpoints and startup optimizations
laya-dino
JakkNaj
A fine-tuned Laya model plays Chrome Dino using a Python backend and TypeScript frontend
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