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% ...

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.
InfoQ

NVIDIA Dynamo Addresses Multi-Node LLM Inference Challenges

Serving Large Language Models (LLMs) at scale is complex. Modern LLMs now exceed the memory and compute capacity of a single GPU or even a single multi-GPU node. As a result, inference workloads for ...
Semiconductor Engineering

AI Inference Needs A Mix-And-Match Memory Strategy

Interactive LLMs (chat, copilots, agents) with strict latency targets Long‑context reasoning (codebases, research, video) with massive KV (key value) cache footprints Ranking and recommendation models ...

DeepSeek's DSpark just made Nvidia's most important new bet harder to close

DeepSeek just released DSpark, an inference module that makes its AI models 60% to 85% faster without new hardware. Nvidia is ...

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.