---
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- opdlm
- block-diffusion
- diffusion-language-model
- math
- qwen3
base_model: Qwen/Qwen3-4B
---

# OPDLM-MATH-4B

**OPDLM-MATH-4B** is an On-Policy Distillation Language Model (OPDLM) — a block-diffusion language model (block size 4, 4 denoising steps per block) post-trained for mathematical reasoning. It is built on a block-diffusion adaptation of **Qwen/Qwen3-4B** (architecture `a2d-qwen3`).

This is the **base (non-thinking)** variant: short-context (2k) math post-training, no explicit chain-of-thought thinking block. ArXiv report: arxiv.org/abs/2606.06712

arXiv report: arxiv.org/abs/2606.06712




## Usage

This model uses custom modeling code; load with `trust_remote_code=True`. Generation is block-diffusion (non–left-to-right), so use the project's inference utilities (block_size=4, denoising_steps_per_block=4) rather than vanilla `model.generate`.

```python
from transformers import AutoModel, AutoTokenizer
tok = AutoTokenizer.from_pretrained("divelab/OPDLM-MATH-4B", trust_remote_code=True)
model = AutoModel.from_pretrained("divelab/OPDLM-MATH-4B", trust_remote_code=True)
```