Tom's Hardware Verdict
The Ryzen AI Halo lives up to its promise as a turn-key local AI platform within AMD’s AI ecosystem, and it comes with helpful docs and useful software to get you rolling quickly. But its performance trails DGX Spark and GB10 boxes, and it’s not much cheaper than those systems.
Reasons to buy
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Takes all the guesswork out of setting up a Strix Halo box for local AI
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Included software and playbooks get you moving quickly
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Provides a direct line to AMD software updates
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x86 platform lets you run Windows and Windows apps easily if needed
Reasons to avoid
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AI performance and software compatibility still trails Nvidia GB10 platform
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Playbooks and documentation could use more refinement
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Pre-installed software could sometimes be more logically configured
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At $3,999, you’re not that far off from a faster, more refined GB10 box
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Nvidia's DGX Spark and its GB10 SoC have set the template for what a purpose-built local AI developer sandbox should be. The combination of a standardized hardware platform with robust first-party software support and thorough documentation lets those curious about local AI get up and running faster than buying a bare-metal box and building everything up from scratch, especially in the rapidly evolving AI space.
AMD's Ryzen AI Max+ 395, aka Strix Halo, SoC, is the best x86 spoiler for GB10 so far. It has the same 128GB of unified memory, a powerful 16C/32T Zen 5 CPU, and a Radeon 8060S integrated GPU with 2560 RDNA 3.5 stream processors. It also has an AMD XDNA 2 NPU for those who want to experiment with that accelerator in addition to the general-purpose Radeon GPU. And it can run Windows and Windows apps natively, whereas GB10 boxes are Linux-only for now.
AMD's partners have been building around this hardware for about a year and a half, and it's a well-known quantity at this point. But once you have that hardware in hand, setting it up for AI workloads involves digging through scattered GitHub pages, Reddit threads, and AMD official documentation to get all the software pieces lined up right for the best performance and compatibility.
AMD is trying to change all that today with the launch of the Ryzen AI Halo, a first-party, turn-key Strix Halo mini-PC that puts local AI first. This system can be had with Windows or Linux, and at least in the Linux form we're testing today, it comes preloaded with the full AMD ROCm software stack and an assortment of applications you need to immediately start generating tokens with your preferred model.
And on the support side, AMD has taken a page directly out of Nvidia’s book and cooked up an entire set of its own playbooks that cover various local AI applications and usage scenarios with the AI Halo (and Strix Halo systems more generally) to serve as a springboard for local AI explorers.
The grand tour
The AI Halo comes wrapped in a plastic shell with a subtly color-shifting finish. It's got a large light bar ringing its front and sides that indicates system status. White means it's awake, while a pulsing blue indicates that it's asleep, assuming you allow it to suspend at all. Red indicates a fault. If you find the LED strip distracting, you can just turn it off using the preinstalled AI Developer Center app.
The AI Halo has air intakes on its top and sides, and AMD cautions that you shouldn't block any of these intakes. If you're running by the book, that means this system is less flexible than it could be for space-constrained or multi-node home lab setups, where turning the unit on its side would allow for valuable space savings.
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Enterprising community members will likely design and share 3D-printed spacers and risers to get around these limitations, but for a device that is presumably meant to be used in home labs and production environments, the lack of flexibility in orientation is a small but annoying oversight.
Around back, the AI Halo has the same trio of USB Type-C ports you'll find on Nvidia GB10 boxes, plus one more for power input with the included 240W brick. The port closest to the power plug runs at “USB 3.2” speeds, while ports 3 and 4 are higher-speed USB 4. These ports are all DisplayPort Alt Mode compatible, or you can use the HDMI 2.1 port for display output if you prefer.
For wired networking, the AI Halo offers a 10 Gigabit Ethernet port. That’s certainly fast, and AMD has written a clustering playbook for multiple AI Halos using that interface, but it’s in a whole other league compared to the 200Gbps ConnectX-7 NIC on the DGX Spark and its ilk.
We didn't want to strip our AI Halo all the way down to its guts, but each of the four rubber feet on the bottom of the system is secured with a pair of tiny magnets, and they conceal the four screws you presumably need to remove to get further inside.
Here’s a quick look at this system’s specs:
CPU |
AMD Ryzen™ AI Max+ 395 Processor — 16 cores, 32 threads, “Zen 5” architecture |
GPU |
AMD Radeon™ 8060S Integrated Graphics |
NPU |
AMD XDNA™ 2 NPU |
SoC TDP |
120W |
Memory |
128GB LPDDR5X, 8000 MT/s, 256GB memory bandwidth |
Storage |
2TB NVMe SSD |
USB |
3x USB-C ports (one USB 3.2 Gen 2, two USB 4), 1x USB-C for power input |
Networking |
1x 10 Gigabit Ethernet Wi-Fi 7 Bluetooth 5.4 |
Display outputs |
USB-C DisplayPort Alt Mode HDMI 2.1 |
Operating system |
Linux (customized Debian) or Windows 11 |
Dimensions |
150 x 150 x 45.4 mm (5.9 x 5.9 x 1.79 in) |
Amid the ongoing RAMpocalypse and NANDpocalyse, no Ryzen AI Max+ 395 system with 128GB of RAM and a large SSD is cheap, assuming you can find a 128GB config in stock anywhere.
Even against that backdrop, the $3999 price tag for the AI Halo that we’re testing today is a pricey proposition. That sticker puts it at the low end of Nvidia GB10 systems like the Asus Ascent GX10 (albeit in its 1TB config).
Our past testing of Strix Halo versus GB10 for local AI workloads has decisively put Nvidia’s platform on top, so this is a potentially awkward place for the AI Halo to land. Let’s dig in and find out if anything has changed.
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As the Senior Analyst, Graphics at Tom's Hardware, Jeff Kampman covers everything that has to do with graphics cards, gaming performance, and more. From integrated graphics processors to discrete graphics cards to the hyperscale installations powering our AI future, if it's got a GPU in it, Jeff is on it.
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Neilbob Me when trying to understand the meaning and purpose of such devices (and A.I. in general).Reply
LKCi0gDF_d8
AMD just blowing bubbles, right along with N****a. I expect Intel will be next up with a meaningless overpriced plastic box. -
Pierce2623 Software compatibility is a negative compared to an ARM based machine?? Sure guys…. Also it seems only benchmarking some AI models and nothing else is purposely catering to Nvidia. AI hadn’t even started booming when we first heard about Strix Halo. So it clearly wasn’t designed solely for AI regardless of how they’ve advertised during the AI boom. If the AI boom hadn’t happened Strix Halo would be getting sold with 32GB for $1000. Knowing all that context, it seems weird to only test a few AI models.Reply -
Bigshrimp What are these devices for the price? I know this is a rhetorical question, but it's still funny that this was released. Costly for what it is...Reply -
suryasans AI writing by Google Gemini is much smarter and fairer than you. https://www.google.com/search?q=amd+ryzen+ai+halo+ai+developer+pc+vs+nvidia+gb10+power+consumption&sca_esv=4b04a474141781e0&rlz=1C1CHBF_enID1038ID1038&sxsrf=APpeQnsquHCA-jw-qqP98xNQhxFXMchnpg%3A1783360176978&ei=sOpLaqiwO_SVseMP0ty0qAw&biw=1600&bih=731&oq=amd+ryzen+ai+halo+ai+developer+pc+vs+nvidia+gb10+power+co&gs_lp=Egxnd3Mtd2l6LXNlcnAiOWFtZCByeXplbiBhaSBoYWxvIGFpIGRldmVsb3BlciBwYyB2cyBudmlkaWEgZ2IxMCBwb3dlciBjbyoCCAAyBRAhGKABSOhOUKIJWIk8cAF4AJABAJgBhwGgAasFqgEDNy4yuAEDyAEA-AEBmAIKoALIBcICCBAAGO8FGLADwgILEAAYgAQYogQYsAPCAgUQABjvBcICCBAAGIAEGKIEmAMAiAYBkAYFkgcDOC4yoAedE7IHAzcuMrgHxQXCBwM1LjXIBwyACAE&sclient=gws-wiz-serpReply -
maviz This is a completely useless piece of trash on a piece of shit ecosystem.Reply
I had the Ryzen with 32 GB and i will tell you the drivers are *USELESS*.
Even above that, the compatibility matrix is laughable...i had to sell both my CPU and my 6700 XT...and now i have a 5060 that is leaps and bounds faster and "just works"....and another 5070 TI which was not comparable to begin with. This box is hopelessly slow for any real AI work, priced like shit, performing like shit, i dont even know how they dare present this as any sort of evolution. You spend a few hundred more and get something 3 yrs ahead in the ecossystem and also MANY times faster...its laughable at best. -
JamesJones44 Reply
AI training and inference is all done on Linux and largely with ARM based servers believe it or not (they cost less and the CPU isn't all that relevant for AI workloads). The fact that x86 lags in this department isn't a surprise.Pierce2623 said:Software compatibility is a negative compared to an ARM based machine?? Sure guys…. Also it seems only benchmarking some AI models and nothing else is purposely catering to Nvidia. AI hadn’t even started booming when we first heard about Strix Halo. So it clearly wasn’t designed solely for AI regardless of how they’ve advertised during the AI boom. If the AI boom hadn’t happened Strix Halo would be getting sold with 32GB for $1000. Knowing all that context, it seems weird to only test a few AI models. -
dva852 Reply
AI is a CUDA world, at least for now. ROCm support is still spotty. x86/ARM is irrelevant.Pierce2623 said:Software compatibility is a negative compared to an ARM based machine??
AMD is leaning on open-source angle as it tries to breach CUDA moat. It also places higher focus on Windows platform, gunning for Windows devs as they move to AI. Nvidia is doing same with RTX Spark. Windows itself is moving to ARM. Lots of moving pieces.
You don't buy a $4K box to play games on an iGPU. Strix Halo was already considered "overpriced" at $2K--which admittedly was before-DC era. But repurposed for AI, it has gained new relevance, and higher valuation. IMO, not $4K high, but "higher."Pierce2623 said:Also it seems only benchmarking some AI models and nothing else is purposely catering to Nvidia.
At $4K vs DGX Spark's $4.7K, Strix AI is underwhelming. DGX has more compute, faster interconnect, better ecosystem. But the price is a bit irrelevant. It's a reference device, with official software (Win & Lin) stack, and most importantly, official support. It's meant to establish AMD's AI ecosystem. Think of it as placeholder for future iterations.
Even though Spark has faster compute, both it and Strix Halo are saddled with same memory bandwidth bottleneck. It's why the models used in AMD's benchmark (as well as THW ones) are either mixture-of-expert (read: low active parameter count), or small dense models. Even a midsized dense model would've brought both to a crawl. That's the real takeaway, that LPDDR5X is a makeshift solution to the AI bandwidth problem, and will need better solutions going forward.
Gorgon Halo also on LPDDR5X. Medusa Halo gets LPDDR6/X, in either late '27 or '28.
I looked on YT and "Ryzen AI Halo reviews" are popping up, so apparently today is "Halo AI's" official coming out party. Underlining the point is AMD's YT blurb, with Jack Huynh's mug trying reeeeaally hard to crack a smile. More happy thoughts, Jack.
For a more informative Ryzen Halo AI review, as well as providing a wider perspective,
Gz62bniDkpgView: https://www.youtube.com/watch?v=Gz62bniDkpg
After a forgettable foray in some high-end laptops, Strix Halo popped up in Shenzhen mini-PCs, and was immediatedly co-opted for AI use. The review below was 9 months ago, and gives a good perpective on Ryzen AI's WIP state at that point in time. Note also the $1.8K price.Pierce2623 said:AI hadn’t even started booming when we first heard about Strix Halo. So it clearly wasn’t designed solely for AI regardless of how they’ve advertised during the AI boom.
prIUKAbHlj8View: https://www.youtube.com/watch?v=prIUKAbHlj8 -
salgado18 Reply
For coding, for example: you set up a coding agent platform, like Claude Code, Codex or OpenCode. Then, you ask it to implement something or fix a bug. The platform will orchestrate AI agents and local tools to understand, plan, execute and test the task. That's the use case.Neilbob said:Me when trying to understand the meaning and purpose of such devices (and A.I. in general).
LKCi0gDF_d8
AMD just blowing bubbles, right along with N****a. I expect Intel will be next up with a meaningless overpriced plastic box.
Why such a box? Cloud-hosted AI models cost a lot of money if charged per token, and monthly subs have limits and are subject to price increases or vanish entirely. To run locally, even most gaming PCs struggle with such a heavy task that is running AI, let alone many of them in parallel. And setting up a central server with good hardware is crazy expensive and a big maintenance task.
Enter these boxes: you pu one on your desk, work on it or connected to it, and the agent platform uses its hardware to work, instead of cloud models. So your work is entirely local and contained to one PC.
I believe this is the future of PCs, and we're just seeing the first prototypes and proof-of-concepts. It's terrible value for gaming, regular working, media editing etc. But for local AI usage, it's a very tempting format. -
salgado18 Reply
What? I tested Claude Code and OpenCode, and it's just install -> set api key -> start prompting. Even with Ollama it's quick and easy.dva852 said:"For coding, for example: you set up a coding agent platform... and then it's immediately you spin up a containerized runtime, pipe your LLM through a RAG vector store, scaffold the MCP tool schema, YAML the CI/CD hooks, kubectl apply to the Kubernetes cluster--
FTFY o_O -
JamesJones44 The crazy part is this is starting to look like somewhat of a bargain. A year ago you could have gotten an 128GB M4 Max Mac Studio with double the memory bandwidth of the max+ 395 for $3700, now to get that level of performance you are in the 5.5+k range with GB 10 or Apple Silicon. Performance for local model operations is probably good enough for low to medium intensity tasks.Reply