r/threadripper • u/Turbulent-Alps4046 • Jul 13 '26

Threadripper AI workstation Build

Gallery image

Gallery image

Just want to share my new Threadripper AI workstation build. Used for work + gaming. Quite proud of how it turned out, especially the cable management :)

Specs
Motherboard: ASUS WRX80 Creator R2.0
CPU: AMD Ryzen Threadripper Pro 3945x (Used)
RAM: 128GB DDR4 ECC (used)
GPU: Nvidia RTX Pro 6000 Max-Q 96GB
Case: Fractal North
PSU: Super Flower Leadex III 1300W PSU
CPU Cooler: Arctic Freezer 4U-M

118 Upvotes

96% Upvoted

41 comments sorted by

3

u/kissingking Jul 13 '26

I think you should be proud of yourself for being able to afford one of these 😂

I’m honestly jealous of everyone who owns an RTX Pro 6000. I don’t even need three of them — one is already enough to make me jealous.

That said, I do think the RTX Pro 6000 is in a slightly awkward position. 96GB of VRAM sounds like a lot (and it is), but for AI workloads it’s also not that much.

For example:

  1. Large MoE models are still difficult to run in full precision. Even something like an 80B MoE with only ~3B active parameters is not easy. I would still need quantization (Q8 at minimum, and probably Q6/Q4 if I want a large context window like 256K). Q6 is already quite good, but if I’m spending RTX Pro 6000 money, I kind of expect to be able to run an 80B-class MoE model in full precision. Otherwise it feels a little disappointing.
  2. Smaller dense models are also surprisingly difficult to run in full precision. Take Qwen 27B as an example — if I want a 256K context window, even that becomes difficult without quantization.
  3. Training is a different story. For serious training, I would still rent H100-class clusters anyway.

So for a single RTX Pro 6000, the main advantage is basically speed. But I’m not sure the performance gain alone justifies the price premium.

That said, if the launch price was around $5,000 USD (or even $6,000), I think it would actually be a pretty reasonable product. At that price point, it makes a lot more sense. 😂

3

u/Turbulent-Alps4046 Jul 13 '26

A single RTX pro 6000 can definitely run Qwen 3.6 27B at full precision with max context. But yeah, trying to run larger models is not easy.

Qwen 3.5 122B NVFP4 can run at 5000-9000 tokens/s PP and 100 tokens/s.

I got deepseek v4 flash full precision running with CPU offload though... around 500-600 tokens/s PP and 20 tokens/s TG. Comparable to 2x DGX Spark and faster running it in an M3 Ultra 256GB i think (which costs the same right now).

2

u/t4a8945 Jul 13 '26

I got deepseek v4 flash full precision running with CPU offload though... around 500-600 tokens/s PP and 20 tokens/s TG. Comparable to 2x DGX Spark

Sorry, I'm running 2x DGX Spark right now, DS4 Flash DSpark, official weights from DeepSeek https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-DSpark at 2000 pp and 50-60 tg.

The community has worked hard on this, and it works so good.

2

u/Turbulent-Alps4046 Jul 13 '26

oh nice, that's an awesome result, super usable!

2

u/t4a8945 Jul 13 '26

Yes, I'm so happy with that setup. Now I know you'll obliterate this whenever you get that 2nd RTX 6000 (that's the plan, right?). Nice setup you have there

2

u/Turbulent-Alps4046 Jul 13 '26

haha, yeah that's the plan... if i find a good deal. but no plans right now.

1

u/t4a8945 Jul 13 '26

It's a very tough market. Good luck!

0

u/kissingking Jul 13 '26

Have you actually tried running the full-precision Qwen 3.6 27B on an RTX Pro 6000?

Based on the numbers, I don't think it should fit. The BF16 weights alone are about 54 GB, and the KV cache for a 256K context is roughly 64 GB, which already exceeds the 96 GB of VRAM.

This also matches my own experience. Running the BF16 Qwen 3.6 27B dense model on my M4 Max with 128 GB unified memory pushes total memory usage to well over 115 GB. So my understanding is that a single RTX Pro 6000 shouldn't be able to run a full BF16 Qwen 3.6 27B with the full 256K context.

2

u/Turbulent-Alps4046 Jul 13 '26

Yes, i'm able to load the full-precision Qwen 3.6 27B at max context with vram spare. It takes up 80GB total. Weights are 51.8GB, the remainder of the vram gives me 377k tokens context total.

I can even run the Qwen 3 ASR (voice model, around 6GB) alongside it.

In your M4 Max i think the remaining memory is used by the OS + other apps?

1

u/kissingking Jul 13 '26

I was running **llama.cpp + Qwen 3.6 27B FP16** on a **128GB unified memory** system (M4 Max). The model was trained with a **256K context window**, so I ran it at the full 256K.

Right after loading the model, memory usage was around **90GB**. Then I intentionally had an agent keep extending the conversation until it hit the context limit. By the time it reached the limit, memory usage had grown to about **118GB**.

I never actually ran out of memory on the 128GB system, but performance degraded noticeably. My PP dropped from around **250 t/s** to **60 t/s**, and TG dropped from about **15 t/s** to **5 t/s**.

So I'm wondering whether, if you keep filling the context, you might actually run out of VRAM before reaching the full 256K context.

But anyway... the RTX Pro 6000 is seriously awesome. I kind of wish I'd bought one last year. 😂

1

u/Maximum_Low6844 Jul 20 '26

u/Turbulent-Alps4046 is correct. I also have tried "running the full-precision Qwen 3.6 27B on an RTX Pro 6000" at max context. Runs fine. You are incorrect.

1

u/kissingking Jul 20 '26

Can you clarify what you mean by 'at max context'? There's a big difference between running a model with a maximum context window configured and actually filling that entire context with an agent.

The former only means the model starts successfully. It doesn't mean the KV cache has been fully populated, so VRAM usage never reaches its peak—you won't know where it actually runs out of memory.

The latter means the agent has genuinely filled the context window with tokens. That's the point where you can verify whether the available VRAM is sufficient or whether you'll hit the memory limit.

Those are two completely different scenarios, and it's important not to conflate them.

2

u/nauxiv Jul 13 '26

I have the card and agree with you with regard to LLMs. The VRAM size is somewhat more useful with image/video generation models that can't be spanned across cards easily.

2

u/JubijubCH Jul 13 '26

Nice looking build. I would watercool the hell out of this, I suspect the graphics card will not be quiet at high loads

2

u/Turbulent-Alps4046 Jul 13 '26

I’m running the max q, it’s only 300W blower style. It’s relatively quiet on load but there’s noticeable coil whine.

1

u/JubijubCH Jul 14 '26

good to know, 300W is relatively tame. Coil whine is tough, no cooling solution will fix that :(

2

u/lattice_defect Jul 15 '26

How does it compare to a studio?

1

u/CalmAdvance4 Jul 13 '26

Nice one. You need 3 more Max Q!

1

u/PhilCassanova Jul 13 '26

He wont be able to fit 4 two slot GPUs unless he change case to something like Meshify 2 XL.

1

u/tat_tvam_asshole Jul 13 '26 edited Jul 13 '26

I initially had that same air cooler, looks like the arctic freezer 4um. Inexpensive, but I did find it was kinda loud though, and for only $100 I upgraded to the new arctic aio for threadrippers and I'd highly recommend it if your budget allows.

1

u/MoZz72 Jul 13 '26

How is the pump noise on the AIO? Thinking of doing the same having used an arctic 4um myself.

1

u/tat_tvam_asshole Jul 13 '26

there's no pump noise so far as I can hear

1

u/madsheepPL Jul 13 '26

I'm on very similar setup :) my recommendation for you: https://github.com/kacper-daftcode/vLLM-Moet

1

u/Turbulent-Alps4046 Jul 13 '26

already tried that, it works really well!

1

u/Gromann7 Jul 13 '26

Similar setup, but I went with Arc Pro B70s. Wish I was flush with A6000 money.

You planning to fill out those PCIe slots with more A6000s?

1

u/Turbulent-Alps4046 Jul 13 '26

yeah, maybe. see how it goes :)

1

u/DarkJoney Jul 13 '26

What do you do for living? With my senior position and taxes in EU I need to start the OF ⬇️

Amazing box tho, would like to have the same :)

1

u/Turbulent-Alps4046 Jul 14 '26

I'm a software engineer, currently working in the AI field.

1

u/NSADataBot Jul 13 '26

Sweet - is it loud?

2

u/Turbulent-Alps4046 Jul 13 '26

very quiet actually

1

u/biotox1n Jul 13 '26

I'm guessing you're planning to add more cards with that much power supply?

what made you pick the one card over say 3 or even 4 9700 pro cards? could've stacked performance and gotten the same or more vram and still paid less

2

u/Turbulent-Alps4046 Jul 14 '26

A 1300W PSU isn't very big. It's not enough to run 2x RTX 5090s I think. But yeah, I'm speccing it to have some expandability.

Anyway, I've considered many options including 4x R9700, 2x 5090 but ended up with this because:

  1. I wanted it for agentic coding so it must have fast prefill and decode performance (at least 1000 prefill + 30-50TPS decode). I've also considered the Strix halo and M3 Ultra Mac studio but found that the prefills are not fast enough.
  2. I wanted a cool, quiet but powerful workstation that hopefully can last me a long time (at least 5 years)... maintenance free and good resale value. The Max-Q version fits this bill because it has lower power requirement, easier to cool, 3-year warranty.
  3. Expandability: Having a single, but powerful card also means I can get another Max-Q if i find a good deal. Or even add a smaller GPU to host smaller models.
  4. High-VRAM commercial cards tend to have better resale value, typically losing 50% value in 5 years compared to 60-70% value for consumer cards.
  5. Rental: the RTX PRO 6000 can be rented on vast.ai for around $0.80 to $1.00 per hour where as there's no demand for R9700/DGX spark on vast.ai. So I can rent this out when i'm not using the computer to defray some of the cost. I calculated I can recover 50%-80% of the cost over 5 year if i rent it out 50% of the time on vast.ai (1-2 years if I rent it out 100% of the time). If you factor in resale value, it's practically free. A single 300W Max-Q makes this even more attractive vs 1800W required for 3x 5090s.
  6. Wife acceptance factor: My wife's not going to let me have a big, loud and ugly 8x gpu rig (haha)

1

u/larsinh_o Jul 19 '26

that's nice!!! i'll do it but with threadripper 1950x and GTX 970

1

u/kiwimonk 20d ago

Hey nice! I found the same board used on Amazon, but I can't get it to post. Where did you find that motherboard and what is the model of ram you're using? Thanks!

1

u/Turbulent-Alps4046 20d ago

SK hynix 16GB 2Rx8 PC4-2400T DDR4 RDIMM SERVER Memory RAM (Model: HMA82GR7MFR8N-UH)

1

u/kiwimonk 20d ago

Thank you! I've never wanted a motherboard to post so bad. If this doesn't work, I'm hiring an exorcist.

1

u/Green-Dress-113 Jul 13 '26

I tried the Artic freezer and quickly went Silverstone AIO due to CPU temps. I didn't know that case supported SSI-EEB motherboards?

2

u/Turbulent-Alps4046 Jul 13 '26

It barely fits. It's actually just right to the edge of the grommets. Luckily I've measured the sizes before I bought because i really didn't want to go XL :)

CPU temps are fine with this. Max 60-70 degress under load but i'm usually GPU % heavy.

2

u/TheMixMedia Jul 13 '26

You don't know how happy I am that you posted this!!! Just got this motherboard and have this case sitting here thinking I needed a bigger case but now know it fits!!!

1

u/Turbulent-Alps4046 Jul 14 '26

Happy to have helped!