Does a typed-judgment model rerank Finnish legal passages better than a cross-encoder?

Postgres FTS, pgvector and RRF first stage; Jev, Voyage, GPT-4.1-mini, GPT-5.6-luna and open-weight Laya as rerankers on two Finnish legal corpora. Recall, MRR, nDCG, latency.

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Preview of Does a typed-judgment model rerank Finnish legal passages better than a cross-encoder?

Launch: Laya
Use case: Multilingual
Format: Repo
Source: github.com

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mizorewww

@mizorewww · Sep 19

Validated Core ML ports of all Laya checkpoints. One short multilingual decision in 4.98 ms P50 on M3 Max with ANE FP16, at 2.78x better energy per decision than MLX FP16.

雨夹雪❄️

@mizorewww · Sep 20

The port announcement: Laya on MLX, under 1 GB RAM, choosing the snake’s next move 60 times a second on a local M3 Max.

atomic.chat

@atomic_chat_hq · Sep 21

Atomic.chat ran Laya on a 16 GB MacBook Air against Jev over the API on a Grok-built Tetris. Local won on speed: 11x faster decisions.

codejunkie99

@codejunkie99 · Sep 22

Open on GitHub

Does a typed-judgment model rerank Finnish legal passages better than a cross-encoder?

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