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
korean-decision-benchmark
jkf87
Benchmarks SemIf, Decider, Laya, and Jev on Korean hate-speech classification
synthetic-ehr-decision-evals
MadCodeTX
Benchmarks decision models on synthetic EHR administrative-routing tasks
rlcd_x_1b-4b_instruct
mrgonzales-dev
Tests RLCD models including Laya and explores their use with 2B–4B models
gyra
Gowtham-R-2002
Fine-tunes Laya for fast coding-agent decisions and evaluates it against labeled tests
jev-vs-llms
ivanviragine
Compares Jev, Laya, other open models, and chat LLMs on loaded questions in two languages
wizden-moonlander
WizdenOrg
A lunar lander game compares Laya and Jev as typed-decision flight controllers
small-decision-model-cross-domain-degradation
SnackTerminator
A controlled study evaluates cross-domain and cross-lingual transfer in Jev-class decision models
ai-experiments
nadeem4
A collection of documented AI experiments reports protocols and results for model evaluations
laya-playground
shwetankg07
Three browser games measure Laya’s decisions against exact ground truth
laya-scripts
muck-stump
Shell scripts test authentication, server behavior, concurrency, and routing for Laya-compatible APIs
laya-steering-lab
Hantlowt
Tests methods for specializing frozen Laya models and benchmarks their accuracy and runtime
laya-training-log
ChenneyZhuang
Documents training and benchmark results for a fine-tuned Laya browser model
laya-first-look
cvranjith
Explores base Laya checkpoints locally on Apple M4 and reports informal behavior and latency measurements
Tenstorrent.Blackhole-convaiinnovations_laya
Thatch-cloud
Develops a Tenstorrent Blackhole inference backend and service integration for Laya
jev_and_laya_benchmarking
pavanjava
Benchmarks Jev and Laya accuracy and inference speed on typed-decision tasks
jev-laya-openai-comparison
amansahani
Benchmarks Laya and Jev against OpenAI models on financial regulatory decisions
decision-model-bench
SaiNarayana-B
Tests the accuracy and calibration of Laya decision-model confidence scores
jev-arena
eliot5566
Lets users create text-driven fighting bots piloted by Jev, Laya, or other models
laya-fp16-parity
xauberer93
Checks FP16 parity for the Laya model on a ZeroGPU lane
laya-trader
antonellof
Uses Laya MLX to paper-trade crypto and stocks with a dashboard and backtesting tools
system-one-reexamined
CodeWithMoin
Benchmarks Laya and Jev against zero-shot NLI and SetFit classifiers
jev-vs-laya
vizakan10
Compares Jev and Laya decision quality and speed by having both models play Wordle
LayaFinetuning
hermestwogetherbot
Tests Laya decision scenarios and documents a workflow for fine-tuning it on transcript events
laya-mlx-demo
jerryshao2012
Demonstrates an Apple silicon MLX conversion of Laya for typed decision inference
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