How DeepSeek’s DSpark Makes LLMs 85% Faster Without Retraining

DeepSeek has introduced DSpark, an open-source speculative decoding method that accelerates LLM inference by up to 85% ...
Tech Times

NVIDIA Diffusion LLM Hits 2.42x Throughput Without Retraining: Nemotron TwoTower Released

NVIDIA diffusion language model Nemotron TwoTower achieves 2.42x LLM inference throughput without a full retraining run, ...

DeepSeek open sources DSpark, a new framework to speed up LLM inference by up to 85%

DSpark can make decoding faster, but acceptance quality still determines how much speed the system actually realizes.
Analytics India MagazineOpinion

DeepSeek V4 is Now up to 85% Faster With New Inference Technique

The AI giant will use the new capital to fund AI infrastructure, product development, and conduct a major hiring push, with ...
techtimes

NVIDIA’s New LLM Decodes 6x More Tokens Without an Auxiliary Draft Model

Any engineer currently running Eagle3 or a multi-token-prediction setup to speed up their LLM inference now has a compelling reason to look at the alternative NVIDIA's research team published Tuesday.

Google's DiffusionGemma generates 256 tokens in parallel and self-corrects as it goes

Google's open-source diffusion language model generates 256 tokens in parallel and self-corrects, hitting 4x speed on one GPU at a cost to quality.