Intel vs AMD; am I taking crazy pills?

Reddit r/LocalLLaMA / 3/31/2026

💬 OpinionIdeas & Deep AnalysisTools & Practical Usage

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Key Points

A Reddit user attempting to run local LLMs on an Intel Arc B60 Pro struggled for hours using multiple Intel-focused setups (LLM scaler, OpenArc, AI containers), managing only a single Deepseek model and then hitting issues with other models.
As a sanity check, they switched to a Radeon RX 9070XT and—using an ROCm-enabled Ollama setup on Ubuntu 25.10 Server—were able to run multiple models quickly and swap between them with fewer problems.
The post raises the question of whether AMD support for local LLM workflows is significantly easier than Intel, especially given the user’s preference to avoid NVIDIA.
It asks the community whether Battlemage (including B60 Pro) can be effectively leveraged for local LLM hosting and what specific AMD/Radeon purchases (new vs used) offer the best performance-per-dollar for larger models than 16GB VRAM.
The user is considering upgrading to higher-VRAM AMD options (e.g., R9700) but wants guidance on the most cost-effective path to run bigger local models reliably.

I recently started diving into running LLMs locally. Last week I bought an Intel Arc B60 Pro from my local Microcenter. I realize that NVIDIA is the market leader (understatement) and everything is built around NVIDIA for compatibility and functionality, but I do not want to support NVIDIA as a company. It felt like a steal of a deal, having 24GB of VRAM for only $650. I had watched content on YouTube and read online that people had some challenges getting Intel cards working, but I figured that I am somewhat technical and like to tinker, so it would be fun.

I have spent hours on end trying to get things working with intel/llm-scaler, SearchSavior/OpenArc, intel/ai-containers, and some random posts people did online. With these different solutions I tried virtualized and bare metal, various versions of Ubuntu Server as recommended in documentation, and Windows 11 in one instance. I was only able to run a very specific Deepseek model that was called out specifically in one of the procedures, but even then there were complications after trying to get models I would actually want to use loaded up where I couldn't get the original functioning model working.

I felt like I was taking crazy pills, like how could it be this difficult. So last night, as a sanity check, I popped my Radeon RX 9070XT out of my primary desktop and put it in the system that I plan to host the local AI services on. Following a guide I found stepping through installing the ROCm enabled Ollama (bare metal, Ubuntu 25.10 Server) I was immediately able to get models functioning and easily swap between various "Ollama" models. I didn't play around with pulling anything down from HF, but I assume that piece isn't too complicated.

Have any of you been able to successfully leverage a B60 Pro or any of the other Battlemage cards effectively for local LLM hosting? If you did, what is the method you are using? Was your experience getting it set up as rough as mine?

Despite people saying similar things about AMD support for this sort of stuff, I was easily able to get it working in just a couple of hours. Is the gap between Intel and AMD really that huge? Taking into account the fact that I don't want to support NVIDIA in any way, would purchasing a Radeon R9700 (about $1300) be the best bang for buck on the AMD side of the house or are there specific used cards I should be looking for? I would like to be able to load bigger models than what the 16GB in my RX 9070XT would let me run, otherwise I would just pick up an RX 9070 and call it a day. What do you all think?

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