AI inference costs dropped up to 10x on Nvidia's Blackwell — but hardware is only half the equation

New deployment data from four inference providers shows where the savings actually come from — and what teams should evaluate ...
Network World

Nvidia claims 10x cost savings with open-source inference models

Nvidia noted that cost per token went from 20 cents on the older Hopper platform to 10 cents on Blackwell. Moving to Blackwell’s native low-precision NVFP4 format further reduced the cost to just 5 ...
VentureBeat

New LLM optimization technique slashes memory costs up to 75%

Researchers at the Tokyo-based startup Sakana AI have developed a new technique that enables language models to use memory more efficiently, helping enterprises cut the costs of building applications ...
Semiconductor Engineering

HW-SW Co-Designed System With 3 Core Optimization Pathways For Long-Context Agentic LLM Inference (Cambridge, ICL)

A new technical paper titled “Combating the Memory Walls: Optimization Pathways for Long-Context Agentic LLM Inference” was published by researchers at University of Cambridge, Imperial College London ...
NextBigFuture

Defeating Nondeterminism in LLM Inference by Thinking Machines

A research article by Horace He and the Thinking Machines Lab (X-OpenAI CTO Mira Murati founded) addresses a long-standing issue in large language models (LLMs). Even with greedy decoding bu setting ...
Search Engine Land

LLM optimization in 2026: Tracking, visibility, and what’s next for AI discovery

Marketing, technology, and business leaders today are asking an important question: how do you optimize for large language models (LLMs) like ChatGPT, Gemini, and Claude? LLM optimization is taking ...
The Next Platform

Optimizing AI Inference Is As Vital As Building AI Training Beasts

The history of computing teaches us that software always and necessarily lags hardware, and unfortunately that lag can stretch for many years when it comes to wringing the best performance out of iron ...
Business Wire

Red Hat Launches the llm-d Community, Powering Distributed Gen AI Inference at Scale

Forged in collaboration with founding contributors CoreWeave, Google Cloud, IBM Research and NVIDIA and joined by industry leaders AMD, Cisco, Hugging Face, Intel, Lambda and Mistral AI and university ...