Ranked by source signals (HN, Lobsters, authority domains, official posts) and recency. Summaries are generated from a stored copy of the article text; every sentence cites a span of that text, and nothing is shown that failed the citation check.
Analysis5
astgl.com2026-09-22HN 15 pts · 7 comments2,557 words
The developer deployed the Apache 2.0 licensed Laya model, which contains about 421 million parameters, locally on a Mac Studio to avoid hosted service constraints. On a held-out replay of 40 decisions, this local setup achieved a 10-percentage-point gain in acceptable routing decisions compared to a deterministic baseline, though p95 latency reached 466.69 ms under load. The system uses a custom runtime to render questions and options into a single token sequence, eliminating the need to parse unstructured text.written, reviewed, cited
- The service fails closed by refusing to download models during inference and requiring Apple's Metal accelerator.
- The gateway caps Choice at 20 options by default and serializes inference to prevent uncontrolled accelerator load.
- Laya's publisher warns the model is overconfident and accuracy falls as the option list grows.
github.com2026-09-25authorityHN 4 pts · 0 comments4,661 words
Eight decision models are evaluated as candidate lists grow, option orders change, and wrong answers become harder to distinguish. OpenAI's Decisions API and TypeSafe's Jev lead in accuracy, with Decisions costing $0.029 per 1,000 decisions and Jev costing $0.035 per 1,000 decisions. When option order changes, Decisions changes its answer on one in three decisions while Jev changes on one in seven. Holding the order fixed reveals Decisions never changes its answer at all, whereas Jev changes on 4.3% of decisions due to internal non-determinism.written, reviewed, cited
- Decisions returns an exact zero flip rate with fixed order despite having no seed parameter or temperature control.
- Jev recomputes and agrees with itself after changing input token count by one trailing space.
- Decisions loses 27.9% accuracy on near-neighbour distractors for request routing, while Jev loses only 9.0%.
laya.convaiinnovations.com2026-09-191,940 words
Laya is a non-autoregressive decision engine that executes in 32.8 milliseconds on a single GPU with full support for over 100 languages. The model family includes specialized checkpoints like convaiinnovations/laya-multilingual which runs at 7.2 ms per question when batched, eliminating API subscription costs via 100% open-source Apache 2.0 weights. A built-in Router with preload=True inspects Unicode scripts to route requests to the correct checkpoint, ensuring sub-35ms response times without cold-swap penalties.written, reviewed, cited
- English checkpoint accuracy drops to 0.000 for Khmer while reporting 0.952 mean confidence, proving confidence gating fails for non-Latin scripts.
- Choice questions degrade significantly with over 20 options, as Banking77 testing showed Laya scoring 0.425 against Jev's 0.870.
- Base weights ship with raw temperature logits, requiring domain-specific scalar fitting to cut expected calibration error from 0.466 to 0.081.
brainfunctioncollapse.com2026-09-22HN 4 pts · 1 comments1,015 words
Laya is a 322M parameter open-source model that routes tasks and answers typed questions with probabilities in 21 ms on local hardware. It requires 650 MB of disk space and a 2.3 GB download, loading in about 90 seconds to achieve a decision rate of around 30 times per second. Licensed under Apache-2.0, it offers a free, offline alternative to the hosted TypeSafe Jev, ensuring data never leaves the machine.written, reviewed, cited
- The multilingual checkpoint ships uncalibrated, requiring a language hint to fix routing for non-native scripts.
- Out of the box Laya is strongest at routing and yes/no checks; graded scores improve a lot with fine-tuning.
- The first start downloads 2.3 GB of open weights and takes about 90 seconds to load them.
vercel.com2026-10-01HN 2 pts · 1 comments134 words
