Intel AI Playground Outs 32GB Arc GPU That Could Be Big Battlemage

by Zak Killian — Saturday, December 20, 2025, 02:50 PM EDT

Intel has released version 3.0 of its AI Playground tool, which brings new multimodal upgrades to the app's functionality thanks to modern vision models like Qwen3 VL as well as agentic tool calling support, that allows users to orchestrate actions across different tools and features from within a single chat flow. Instead of completely separate UIs for image generation, chat, etc., the AI can invoke them in context as part of a unified agentic session. There's also speech input support and a fully rearchitected UX in the preview build, which remains open source, as before.

That's not what we're here to talk about, though. After all, this is HotHardware, not HotSoftware. Buried in the user guide was an image that has since been replaced, but which was thankfully archived by hardware enthusiast Haze (@Haze2K1 on Xwitter). Check it out and see if you notice anything that stands out to you:

intel ai playground 32gb gpu leak — *(click to zoom)*

In case you're not spotting it, there are three key details in this image. First, in the bottom right, the Device is listed as "Intel(R) Arc(TM) [0] GPU (32GB)". What in the world could that be? Well, the obvious answer is a BMG-G31-based Arc Pro card with 32GB of RAM. The BMG-G31 die is expected to have a 256-bit memory interface, which makes 32GB of RAM relatively simple using 32-gigabit GDDR6 packages.

That's probably not what this actually is, though. You see, the other key details are the presence of a panther and the "12Xe" necklace he's wearing. As you probably know if you read this site regularly, Intel's next processor launch will be for its new mobile processors codenamed "Panther Lake." We already know that Panther Lake comes in "4Xe" and "12Xe" variants, referring to the number of "Xe3-cores" on the processor package.

It's a lot easier (or at least, cheaper) to get 32GB of RAM hooked up to an SoC rather than to a GPU. It's also entirely possible that this is an integrated part, because Intel AI Playground has long supported Arc-branded integrated GPUs; I have used it on the integrated graphics of an Arrow Lake processor a fair bit. While compute and especially memory bandwidth are both important for AI tasks, the most important performance metric for AI workloads is simply being able to fit the model in memory, and that's a lot easier with an integrated GPU.

ai playground 3 new features — *Some of the cool features in AI Playground v3.0, and they all run locally—no Internet required!*

Does this mean that Panther Lake has awesome AI performance on its integrated GPU? Well, it just might—but this doesn't actually tell us anything of the sort, because have no idea how long it took for the machine to come up with that result. The user has the app set to "Pro 2" image generation mode, which uses the new Z-Image model. We can speak from experience and say that while Z-Image is remarkably efficient, it still likely takes several minutes to generate a single image on an integrated GPU. For context, it takes about 45 seconds on a GeForce RTX 3060 12GB.

Intel's AI Playground is one of the most user-friendly tools that you can use to get started with local AI. It's quite powerful at this point, with chat, image generation, image editing, and even video generation functions built right in, all with a very intuitive UI. If you have an Intel Arc GPU of any sort and you're interested in messing with this stuff without paying for it or being told you've run out of daily tokens, head to GitHub to get downloading.

_{Thanks to Haze (@Haze2K1) for preserving the interesting image.}

Tags: Intel, (NASDAQ:INTC), AI, intel ai playground

Zak Killian

A 30-year PC building veteran, Zak is a modern-day Renaissance man who may not be an expert on anything, but knows just a little about nearly everything.