Dual AMD Radeon AI Pro R9700 or dual NVIDIA or RTX 3090.
Summary
The author is building a dual GPU system for running large language models, evaluating AMD Radeon AI Pro R9700 versus NVIDIA RTX 3090 options while aiming to reduce AI subscription costs.
Similar Articles
Modded RTX 4090 48GB vs Radeon AI Pro R9700 vs Arc Pro B70 for local coding LLMs?
A user seeks advice on choosing between a modded RTX 4090 48GB, dual AMD Radeon AI Pro R9700, or dual Intel Arc Pro B70 for running local coding LLMs, highlighting trade-offs in price, VRAM, software ecosystem, and inference speed.
A very confusing report from Puget Systems
This article evaluates the AI inference performance of dual AMD Radeon AI PRO R9700 GPUs, comparing them to Intel Arc Pro B70 and NVIDIA RTX 5090, highlighting cost-effectiveness and software challenges.
Building a budget 32GB → 48GB VRAM home AI server: 2-3x RX 9060 XT 16GB vs RTX 5060 Ti 16GB, AM5 vs used EPYC?
A user seeks advice on building a budget home AI server with 32-48GB VRAM, debating between AMD RX 9060 XT and Nvidia RTX 5060 Ti GPUs, and whether to use AM5 or used EPYC platforms for local LLM inference and large MoE model offloading.
Upgrading from 2x 3090 - what should I add? (2x A6000/5090/48GB 4090?)
A discussion about upgrading from dual RTX 3090s to alternatives like dual A6000s, RTX 5090, or 48GB RTX 4090, likely for AI/ML workloads.
4xR9700, 2xMi210 or 4x4080S 32G
The user is comparing GPU options like R9700, Mi210, and 4080S to achieve 128GB VRAM for running multiple AI models in parallel, considering factors like cost, performance, and compatibility.