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Updated 2026-09-17

Parallel Constrained Decoding (Qwen2.5-1B-RLCD)

Hugging Face Space exploring open-source parallel constrained decoding as an alternative to Jev.

What it does

Parallel Constrained Decoding (Qwen2.5-1B-RLCD) in the Jev ecosystem. Hugging Face Space exploring open-source parallel constrained decoding as an alternative to Jev. Numbers, harnesses, and comparisons you can rerun on your hardware instead of trusting a screenshot.

Tags in the wild: benchmarks. Follow the primary link for the author's latest notes and setup quirks.

Hugging Face Space exploring open-source parallel constrained decoding as an alternative to Jev. Listed under Benchmarks in Jev Directory so you can compare repos, demos, and maintenance signals fast. Follow the primary link for the author's latest setup notes.

Open the demo when you want proof before you npm install anything. Harnesses and replicas for latency, calibration, and head-to-head baselines. Common tags: benchmarks.

Results

Sourced from https://huggingface.co/spaces/drinkmoonshine/parallel-constrained-decoding on 2026-09-20. Numbers are copied as published; re-run upstream scripts to refresh.

Hugging Face Space README benchmarks parallel constrained decoding with mlx-community/Qwen2.5-1.5B-Instruct-4bit on Apple Silicon M4 Max (macOS Sequoia).

Methodology: Scenarios compare autoregressive structured generation baselines to parallel constrained decoding with 100% schema validity claims. See the Space README Performance Benchmarks section.

Performance benchmarks (Apple Silicon M4 Max)

ScenarioFieldsAutoregressive baselineParallel constrainedLatency speedupSyntax validity
Fintech fraud routing4420 ms (120 tok/s)75 ms5.6x100% guaranteed
Code security audit4380 ms (125 tok/s)68 ms5.6x100% guaranteed
High-cardinality tariff1 field (255 choices)500 ms (118 tok/s)89 ms5.6x100% guaranteed
Enterprise support triage281,900 ms (130 tok/s)270 ms7.0x100% guaranteed

Benchmark FAQ

How is this related to Jev?
The Space explores open-source parallel constrained decoding as an alternative decoding strategy in the same design family as typed System One decisions: bounded candidate sets evaluated in parallel rather than free-form JSON generation.
What model and hardware produced the table?
README states mlx-community/Qwen2.5-1.5B-Instruct-4bit on an Apple Silicon M4 Max running macOS Sequoia.
Where can I run the demo?
Open the Hugging Face Space at huggingface.co/spaces/drinkmoonshine/parallel-constrained-decoding or read the README in the Space files tab.

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