Hosted on MSN

Your old GPU can still run big LLMs – you just need the right tweaks

Running large language models on local hardware not only lets you avoid paying monthly subscriptions to cloud providers, but also prevents large corporations from gaining access to your private data.
VentureBeat

ScaleOps' new AI Infra Product slashes GPU costs for self-hosted enterprise LLMs by 50% for early adopters

ScaleOps has expanded its cloud resource management platform with a new product aimed at enterprises operating self-hosted large language models (LLMs) and GPU-based AI applications. The AI Infra ...
Semiconductor Engineering

Characterization of GPU-based Inference for Reasoning-Centric LLMs (Micron, Argonne)

Researchers from Micron Technology and Argonne National Laboratory have released “Understanding Inference Scaling for LLMs: Bottlenecks, Trade-offs, and Performance Principles”. “The transition from ...
AppleInsider

We have many questions about OWC's new Stack AI speed booster

The OWC Stack AI promises to make local processing of large LLMs easier by somehow inflating your Mac's GPU memory across Thunderbolt. We have questions. One way to trim the bills is to bring it ...
XDA Developers on MSN

I almost upgraded my GPU to run larger local LLMs, but this 8B model proved I didn't have to

The upgrade I almost made wouldn't have solved much ...
Hackaday

Getting A Proprietary-Bus GPU Onto PCIe Enables Cheaper Local LLMs, For Now

If you’ve been thinking of getting into self-hosting generative AI, but don’t have a big budget for hardware, you might want to check out [Hardware Haven]’s latest video on an unusually cheap GPU ...