AMD Ryzen AI Halo – $4k AI Dev Kit

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.

This is just a little under the price of NVidia's DGX Spark with CUDA or a Mac with 128GB and twice the memory bandwidth. The point of Strix Halo used to be that it was half the price of those way more capable machines. You'd be crazy to buy the AMD chip at this price. But the hardware market is generally crazy right now, so I'm sure this will sell as well, unfortunately.

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.

I was in Gray Scott School for HPC last week, and even in scientific usage, CPU-only cases, AMD is still a pain point. Many tools and libraries don't have first class AMD support or any support at all.

It loses to Intel in CPU, and NVIDIA in GPU, in case of scientific libraries and HPC-worthy libs, tools.

I think people who want an "AI Dev Kit" will lean towards Intel + NVIDIA setup.

I am not a fan of Intel, but their MKL, MPI, etc. are not paralleled. Same goes for CUDA with NVIDIA.

I really want a 128gb+ machine but it's brutal to be at only 256 GB/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.

Edit: capitalized gb/s to GB/s.

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.

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.

Seems not really worth it? About the same cost as DGX, same amount of memory and yet the bandwidth is actually slightly lower. And also the DGX is CUDA being an Nvidia device which is a big compatibility advantage

For this to be compelling it would need to be eg 256GB minimum or something

15 square cm box? Wow. Are there similar size, but less powered (and cheaper) workstations? I need a box that can build chromium reasonably fast and I would rather have something portable like this than a PC tower, but this is an overkill at $4k.

32 Gb DDR4 RAM module has a bandwidth of 25 Gb/s and costs $160. If you buy 8 of these, you get 256 Gb RAM with 200 Gb/s bandwidth at $1280. And if you buy 16 x 16 Gb modules (each at $60) then you can get 400 Gb/s of bandwidth for $960.

The only problem, you need 8 or 16 memory controllers. Memory controllers are not that expensive: Intel Core i3-14100F has 2 channel controller and costs $110, so we can estimate that 16-channel controller should cost not more than $880, and 8-channel controller should cost $440.

So isn't it better to make a cheap CPU with 16 DRAM controllers instead of this $4K gear having only 128 Gb? Or maybe 2 CPUs each having 8 RAM channels?

DDR5 costs 2 times more ($360 for 32 Gb) while not even having 2 times the bandwidth so it is not worth buying. It is more reasonable to make more RAM channels and stuff them with DDR4.

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

I was considering getting an AI Max+ machine last year when the price was around $2K. Crazy to see the same specs now going for double the price.

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 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.

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

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

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/

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"

Seems like having a big and clunky external power supply enables a smaller profile for the rest of the unit while making installation a bit more complex. How exactly is this thing going to be installed for use? Wouldn't it be easier to just have a bigger box with more shielding and heat dissipation?

I want to play with openclaw for continuous workflows without burning my cloud credits. Do I want this?

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.

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?

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.

When this was half the price of the DGX Spark, it made sense. But same price is a ridiculous premium for inferior performance but the ability to run Windows.

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?

So... I dont want to ruin gaming more but why not get a gaming PC? Figured this out 15 years ago if its good for gaming, put some more RAM in and boom you have a workstation...

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.

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

what can you realistically do with this ? $4k is a lot of money to spend on something like this without really being sure what models can reliably run

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

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

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I love(!) how these dev!kits are for devs in silicon valley making 300k+ a year and not any other dev in any other part of the world.

Satire if you can’t tell…

The Mac beats it in all benchmarks, is probably more energy efficient, can add more ram, and is more cost efficient (?)… plus you get a Mac. This doesn’t even give you cuda. I’m not sure who this is for.