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The official GitHub repo for the survey paper "A Survey on Diffusion Language Models".
| Date | Stars |
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| 2026-07-31 | 1162 |
| 2026-08-06 | 1170 |
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# Awesome Diffusion Language Models [](https://awesome.re)  [](https://arxiv.org/abs/2508.10875) One of the most starred, comprehensive and up-to-date collections of Diffusion Language Model papers, code and resources! If you find this repository helpful, please consider giving it a ⭐ to support. ## Timeline of Diffusion Language Models This figure highlights key milestones in the development of DLMs, categorized into three groups: continuous DLMs, discrete DLMs, and recent multimodal DLMs. We observe that while early research predominantly focused on continuous DLMs, discrete DLMs have gained increasing popularity in more recent years.  ## Table of Contents - [🎮 Playground](#playground) - [🔥 Must-Read](#must-read) - [📜 Surveys](#surveys) - [🧱 Diffusion Foundation](#diffusion-foundation) - [🎲 Discrete DLMs](#discrete-dlms) - [🌊 Continuous DLMs](#continuous-dlms) - [🖼️ Multimodal DLMs](#multimodal-dlms) - [🎯 Training Strategies](#training-strategies) - [🚀 Inference Optimization](#inference-optimization) - [🔨 Training Frameworks](#training-frameworks) - [⚙️ Inference Frameworks](#inference-frameworks) - [📊 Benchmarks](#benchmarks) - [💡 Applications](#applications) - [🔗 Resources](#resources) ## Playground - [Seed Diffusion](https://studio.seed.ai/exp/seed_diffusion/) [](https://studio.seed.ai/exp/seed_diffusion/) - [Mercury](https://chat.inceptionlabs.ai/) [](https://chat.inceptionlabs.ai/) - [LLaDA](https://huggingface.co/spaces/multimodalart/LLaDA) [](https://huggingface.co/spaces/multimodalart/LLaDA) - [MMaDA](https://huggingface.co/spaces/Gen-Verse/MMaDA) [](https://huggingface.co/spaces/Gen-Verse/MMaDA) - [Dream](https://huggingface.co/spaces/multimodalart/Dream) [](https://huggingface.co/spaces/multimodalart/Dream) ## Must-Read D3PM: [Structured Denoising Diffusion Models in Discrete State-Spaces](https://arxiv.org/abs/2107.03006) [](https://arxiv.org/abs/2107.03006) LLaDA: [Large Language Diffusion Models](https://arxiv.org/abs/2502.09992) [](https://arxiv.org/abs/2502.09992) [](https://ml-gsai.github.io/LLaDA-demo/) [](https://github.com/ML-GSAI/LLaDA) [Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models](https://arxiv.org/abs/2503.09573) (ICLR 2025) [](https://arxiv.org/abs/2503.09573) [](https://github.com/kuleshov-group/bd3lms) [Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding](https://arxiv.org/abs/2505.22618) [](https://arxiv.org/abs/2505.22618) [](https://nvlabs.github.io/Fast-dLLM/) [](https://github.com/NVlabs/Fast-dLLM) Super Data Learners: [Diffusion Language Models are Super Data Learners](https://arxiv.org/abs/2511.03276) [](https://arxiv.org/abs/2511.032
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:a61a7a9d3cce65c0, llm:Repository is the official GitHub repo for the survey paper 'A Survey on Diffusion Language Models' (description). No code; it's a literature/survey resource on diffusion language models.
matched fp:a61a7a9d3cce65c0, llm:Repository is the official GitHub repo for the survey paper 'A Survey on Diffusion Language Models' (description). No code; it's a literature/survey resource on diffusion language models.
matched fp:a61a7a9d3cce65c0, llm:Repository is the official GitHub repo for the survey paper 'A Survey on Diffusion Language Models' (description). No code; it's a literature/survey resource on diffusion language models.
