---
datasets:
- d3LLM/trajectory_data_llada_32
tags:
- diffusion
- text-generation
- fast-inference
- d3llm
pipeline_tag: text-generation
---


# d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation 🚀

## Model Description

**d3LLM-LLaDA** is an ultra-fast diffusion language model that achieves high generation speed while maintaining competitive performance. Built on the Dream architecture.

## Key Features

- 🚀 High throughput: **5.0× faster** than autoregressive models (Qwen-2.5-7B-it) on H100 GPU, **3.5× faster** on A100 GPU. Achieves **288.73 tokens/s** on H100 (vs 57.32 for AR baseline) on GSM8K-CoT Dataset.
- 📊 High AUP (Accuracy Under Parallelism) scores across benchmarks
- 🔧 Optimized for coding and math reasoning tasks

## Usage

For detailed usage instructions, evaluation scripts, training datasets, and training code, please refer to the official GitHub repository and our blog:

- 👉 Code repo: **[https://github.com/hao-ai-lab/d3LLM](https://github.com/hao-ai-lab/d3LLM)**
- 🌐 Blog: **[https://hao-ai-lab.github.io/blogs/text-diffusion/](https://hao-ai-lab.github.io/blogs/text-diffusion/)**