Towards Speed-of-Light Text Generation with Nemotron-Labs Diffusion Language Models
Nemotron-Labs has introduced a new type of language model called diffusion language models (DLM) that allows for faster text generation. Unlike traditional autoregressive models that generate one token at a time, DLMs can generate multiple tokens in parallel and revise them iteratively. This innovation aims to enhance performance for latency-sensitive applications and improve the overall efficiency of language processing tasks.
- ▪Nemotron-Labs Diffusion models can generate multiple tokens in parallel, improving efficiency.
- ▪The models support three generation modes: autoregressive, diffusion, and self-speculation.
- ▪NVIDIA is releasing various scales of the models under different licenses for research flexibility.
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Back to Articles Towards Speed-of-Light Text Generation with Nemotron-Labs Diffusion Language Models Enterprise + Article Published May 23, 2026 Upvote - Mehran Maghoumi MMaghoumi Follow nvidia Yonggan Fu YongganFu Follow nvidia Pavlo Molchanov pmolchanov Follow nvidia Khadkevich mkhadkevich Follow nvidia Quick Links to the Models, Training Recipe and Technical Report Three Generation Modes in One Model Performance Highlights How we trained Nemotron-Labs Diffusion Deployment and inference through SGLang Get Started Today Large language models (LLMs) have become the default interface for code generation, math problem solving, summarization, document understanding, and many other developer workflows.
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