InfoWorld

Multi-token prediction technique triples LLM inference speed without auxiliary draft models

With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...
9to5Mac

Apple taught an LLM to predict tokens up to 5x faster in math and coding tasks

A new research paper from Apple details a technique that speeds up large language model responses, while preserving output quality. Here are the details. Traditionally, LLMs generate text one token at ...
TheServerSide

Run Llama LLMs on your laptop with Hugging Face and Python

There are numerous ways to run large language models such as DeepSeek, Claude or Meta's Llama locally on your laptop, including Ollama and Modular's Max platform. But if you want to fully control the ...