Laya: An Open-Source Local Alternative to Jev for Decision Making
Laya is a local, open-source decision-making model with 421 million parameters that offers a fast, offline alternative to cloud-based Jev, showing nearly 20x speed advantage in benchmarks.
It seems Jev has an open-source local alternative — Laya.
Laya is a local, open-source decision-making model with 421 million parameters. It works with structured decisions (fast yes/no answers, ratings, or choices from options).
Key features:
- Runs with less than 1 GB of memory
- Available for free on Hugging Face
- Works on laptops and even smartphones
In tests, Laya was compared with the cloud-based Jev. Both systems played the same game of Snake with the same decision format for 30 seconds.
Results:
- Laya: score 46, length 52, 86.5 decisions per second, P50 ~9 ms
- Jev: score 1, length 7, 3.2 decisions per second, full API request cycle 317 ms
On the M5 Pro, the median time was 15.3 ms for local Laya and 298.1 ms for cloud Jev. This is nearly a 20x difference in this test.
The main difference is that Laya makes each decision locally, whereas Jev waits for a response from the cloud API at every step.
However, the project has two stated limitations:
- The context is only 512–1024 tokens, so some tasks simply won't fit.
- Without additional fine-tuning, Laya generalizes worse than Jev.
.com/NandhaKishorM/laya)
Why it matters
AnalysisThis comparison highlights how small local models can provide critical latency advantages over cloud APIs for tasks requiring instant decision-making.
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