In case it saves anyone some time (from the article): "The AMD Ryzen AI Max+ 395(Strix Halo) processor has been available since Spring 2025 and the Halo doesn’t offer anything new on that front."

It has the same 256 GB/s memory bandwidth limit as every board previously, not sure why this is even being released right now as if it's some new fangled thing - you can go get a Framework Desktop for roughly the same price or a GMKtec EVO-X2 for a bit cheaper.

Does this have the same memory bandwidth problems as the spark?

Bosgame is $2799 does the same thing if you plan to run only 1 of them

$4k is pretty darn spendy. I recently purchased a refurbished Corsair AI Workstation with almost the same hardware (same chip, same 128GB RAM, but only 1TB storage) for $2160. Pretty good deal! Codex and I wrote a Linux driver to report the power mode of the device:

https://github.com/pettijohn/corsair-ai-workstation-performa...

How much are we going to pay for "AI kits" once the DRAM shortage is over? Will we be able to run a local model equivalent to the current AI frontier in sub $1000 hardware, even if dedicated, in 5 years?

Was “only” $2k in its previous form but even in this updated box the mem bandwidth is woefully inadequate. There’s a few models with space for a dedicated GPU for hybrid inference but imo not worth it. Save your money for a Xeon or EPYC build

I have another strix halo that I got for half the price (before this price increase world wide). AMD making lemonade is one of the best reasons to get a strix halo. Lemonade + qwen3.6 35B MTP @ Q8_0 + anythingLLM (in docker) replaced 90%+ of my AI usage. And it’s fully local! Setting everything up took less than 3 hours total, including installing the OS

https://lemonade-server.ai/

The one thing that's new/worth pointing out are the https://developer.amd.com/playbooks/ (https://github.com/amd/playbooks) - this is AMD's answer to Nvidia's playbooks (https://build.nvidia.com/spark / https://github.com/NVIDIA/dgx-spark-playbooks ) - I think it's great that they're actually taking this more seriously.

Hardware is the exact same as what used to be available for $2K last year (and is still $1K cheaper from Chinese OEMs).

LTT Lab's LLM testing is getting more sophisticated, which is great - I think it's worth noting that ROCm/Vulkan versions and llama.cpp build versions are going to have some big differences for numbers.

For those wanting to get the most out of their Strix Halos, there's both kernel tweaks and utilities like ryzenadj that can help you get the most out of it. ( http://strixhalo.wiki/ has most of that documented). Also, if you're running for coding or agentic work, if you model supports MTP, that's mature and should give you a decent (30%?) decode boost.

I recently bought a few sparks from Micro Center for the exact same price and it comes with ConnectX-7 200Gbps inter-connectivity. Not sure how AMD feels it can charge exactly the same for less.

Are the likes of Dell and Lenovo not going to be annoyed that AMD are cutting them out?

As traditionally AMD was a supplier of parts.

These devices were great when they were cheaper than the DGX Spark.

But when they cost the same price (unless the Spark has shot up too), there's no reason to buy this over a Spark.

The Spark is literally a faster version of this, with better software support.

Edit: And I say that as an owner of a Ryzen AI Max 395 device.

Wow the prices on these have really come up.. Got my Framework desktop mainboard (Just the motherboard + CPU + soldered 128gb RAM) in Dec 2025 for ~1900 EUR

I had hoped this was about Medusa Halo, but unfortunately, it's about 2025 technology. It's the same as Framework Desktop was at the end of last summer, which would have been a slightly silly but fun buy at $2k... I'd hope Mark Cerny / Sony launch PS6 sooner rather than later, as together with the upcoming LPDDR6 standard, it should trickle down to us in the local LLM mud eventually?

It would be really nice if they included clustering support like a blueprint on how to buy several of these and cluster them to run the really large models in the best way possible.

256gbs memory bandwidth is about 1/4 that of a 3090. It would be a better buy with half the memory at 4x the speed.

Even a two-year-old Mac Studio outperforms this kit. A used unit with sufficient memory currently seems to offer the best price-to-performance ratio

"The Apple Silicon Mac Studios outperform the AMD Ryzen AI Max+ 395 machines"

Why do all similar products have a hard limit on the 128 GB VRAM part? For that price, I hoped to get at least 224 GB VRAM

Perhaps if less spending went towards their private aviation interests LTT labs could review a piece of hardware that was released _this_ year, or maybe extend their narrow testing process to cover real-world use metrics like TTFT. Not to mention the lack of real value-perf comparison to CUDA

I really want a 128gb+ machine but it's brutal to be at only 256gb/s for $4k (especially with the drawbacks of both ARM and AMD).

I fear that by the time the RTX Spark comes out it'd have to be $6k, and by the time a 128gb or more machine with 700+gb/s comes out it'd be at $10k, way out of most consumers' hands.

Drastically slower than Macs and NVIDIA unified memory boxes while not being any cheaper.

i wish there was a system like strix halo, but with enough lanes for a dedicated PCIe 5.0 x16 slot so you can have the best of both worlds: large sparse models on CPU with unified memory, dense models on GPU with real tensors and higher bandwidth memory.