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Developer Open-Sources Qwen-2.5-1B-RLCD for Faster Typed JSON Inference on Apple Silicon

September 16, 2026 at 20:46 EDT

Foundation Models
Software Dev & Coding
Open Source

Qwen-2.5-1B-RLCD has been released as an Apache 2.0 Hugging Face repository for faster, type-safe JSON inference on local hardware. The project wraps Qwen2.5-1.5B-Instruct with Parallel Constrained Decoding, reporting 5.6x to 7.0x latency reductions against standard autoregressive JSON generation on an Apple Silicon M4 Max benchmark.

Sep. 17, 2026 · Qwen-2.5-1B-RLCD

Typed JSON at local speed

Parallel Constrained Decoding turns a JSON response into bounded field decisions, aiming to avoid token-by-token generation for enum and boolean outputs on Apple Silicon.

5.6x-7.0x

Latency reduction versus autoregressive JSON generation

100%

Valid JSON syntax in benchmark scenarios

255

Maximum enum choices per field

1.54B

Parameters in the listed Qwen2.5-1.5B-Instruct base model

Enterprise support triage latency

The benchmark's largest schema moves from 1,900 ms to 270 ms, drawn as a proportional 7-block versus 1-block comparison.

1,900 msAutoregressive

270 msParallel constrained

The speedup comes from turning many field decisions into one batched suffix evaluation after a single context prefill.

How the decision path changes

1. Prefix prefill

Read context and schema once.

→

2. Broadcast cache

Fan out the same KV state.

→

3. Slice choices

Score only allowed candidates.

→

4. Assemble JSON

Write verified values directly.

Where it fits

Fraud routing and support triage
Security audits and tariff classification
Local workflows with bounded answers

Where it does not

Open-ended prose or code generation
Planning tasks with unknown output space
Accuracy guarantees without task evals

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