u/panchovix

Hello guys, hoping you're doing well.

I bring this discussion since I have noticed on internet, be USA or EU, RTX 6000 PROs at 16000USD or more are still getting bought.

Even here on Chile, the other day they were in stock at 20000-21000USD post 19% tax and they lasted a few minutes.

My question is why? For sure that won't recoup costs right?

Who are buying these, only enterprises?

What do you guys think?

Hello guys, hoping you're doing well.

I bring this discussion since I have noticed on internet, be USA or EU, RTX 6000 PROs at 16000USD or more are still getting bought.

Even here on Chile, the other day they were in stock at 20000-21000USD post 19% tax and they lasted a few minutes.

My question is why? For sure that won't recoup costs right?

Who are buying these, only enterprises?

What do you guys think?

Hello guys, hoping you're doing well.

I bring this discussion since I have noticed on internet, be USA or EU, RTX 6000 PROs at 16000USD or more are still getting bought.

Even here on Chile, the other day they were in stock at 20000-21000USD post 19% tax and they lasted a few minutes.

My question is why? For sure that won't recoup costs right?

Who are buying these, only enterprises?

What do you guys think?

https://preview.redd.it/g0x5kjrg22jh1.png?width=3840&format=png&auto=webp&s=1b05617e745c834661bfd766077f78bd0b4a9527

We also have the other cases, where it would look like this:

Scenario for 3x 5090 perf	Uplift/Gen	Approximate year
Best	70%	~2029
Historical Average	50.3%	~2030-2031
Modern Average	46.1%	~2032
Worst	30%	~2038

Which one do you think it's the more feasible one?

Also, If we take 2080Ti to 5090 jump in performance, it is 3.1x for 2x the power. I hope RTX 8090 or whatever doesn't uses 1200W for 3x times the 5090 perf.

Hello guys, hoping you're doing fine!

On the last 2-3 months, price of the RTX 6000 PRO seem to have gone insane.

I will start on the price here on my country, Chile:

• RTX 6000 PRO Workstation Edition: 21382 USD post 19% tax.
• RTX 6000 PRO MaxQ Workstation Edition: 20669 USD post 19% tax.
• RTX 6000 PRO Server Edition: N/A (not in stock)

For reference, when I bought my ones, they were at ~11000USD post tax, just 3 months ago.

How it is going on your country/state? If I had to guess, a ton better lol.

Hello guys, hoping you're doing fine!

On the last 2-3 months, price of the RTX 6000 PRO seem to have gone insane.

I will start on the price here on my country, Chile:

• RTX 6000 PRO Workstation Edition: 21382 USD post 19% tax.
• RTX 6000 PRO MaxQ Workstation Edition: 20669 USD post 19% tax.
• RTX 6000 PRO Server Edition: N/A (not in stock)

For reference, when I bought my ones, they were at ~11000USD post tax, just 3 months ago.

How it is going on your country/state? If I had to guess, a ton better lol.

Hello guys, hoping you're doing fine!

I'm continuing after this post some time ago, comparing stock MaxQ performance and such on Anima here.

This time, I shunt modded the 6000 PRO MaxQ, to use up to 2x amounts of power. These cards seems to be binned for high clocks and it is reflected after this.

R002 resistance on top of stock resistance, making the card thinks it pulls half of the power, thus reaching 600W max power.

(Note that you can also solder a R002 resistance on the empty pad and it would work the same)

I also did watercool them to manage the heat, with a Bykski block (this one) at 170USD each from Aliexpress and a GLZM 360mm AIO. So had to get the tubes, coolant and fittings.

Sorry for the finger marks

GLZM AIO

For reference, at 300W it maxes at about 45°C, and at 600W it maxes at about 60°C.

MaxQ running at 624W

I also rented on runpod, a 6000 PRO WS edition, which it's power limit ranges from 150W to 600W (yes, lower than the MaxQ)

Important note again: I did undervolt+overclock the 5090 and the 6000 PRO MaxQ. I can't modify the clocks or power on the rented GPUs on runpod.

So for this test, I ran these settings for the software for pytorch:

• Torch 2.14.0.dev20260612+cu132 for the 5090 and 6000 PRO MaxQ.
• Torch 2.13.0+cu132 stable for the 6000 PRO WS.
• Sageattention 2.1 (on commit e9b072f0fc2682f104abbda306af3d42fc33b969), self built on CUDA 13.3.
• Forge neo on commit 644450e8bf2df24f0ba87307604d0e9f4ae3a9f7
• Installed extensions for RTX Upscaling (https://github.com/Haoming02/sd-forge-nvidia-vfx) and for extra samplers (https://github.com/Panchovix/sd_forge_neo_extra_samplers)
• torch compile: max autotune no cudagraphs

I ran these settings for the samplers and steps:

Forge settings

On text:

• EXP Heun 2 x0 SDE for first 25 steps
• ER SDE for 10 hires pass steps
• Upscale by 1.5x
• 896x1088 resolution
• Batch size 4
• CFG 5
• Shift 3
• Denoise Strength: 0.2
• Upscaler: NVIDIA Ultra
• Seed: 50906000

Prompt used was:

Positive:

masterpiece, best quality, high quality, high resolution, absurdres, highres, very aesthetic, sfw,
 \(ffmania7\),
1girl, solo, clothed,
aether foundation employee, pokemon, dark skin, black hair, short hair,
happy,
from above,
full body,
beige background

Negative:

worst quality, low quality, bad anatomy, (jpeg artifacts:0.8), watermark, sketch, no pupils

For LLMs, I ran llamacpp with a model offloaded to CPU, making the primary GPU the bottleneck when traversing the data, making it compute bound.

Models tested were (offloaded):

• Kimi K2 2.5 (IQ3_M)
• GLM 5.1 (IQ4_NL)

The LLM tests were only tested on my local machine, as testing on cloud via renting a GPU is not feasible or won't have accurate results.

For the hardware, I ran them headless, (with LACT), for Anima:

• RTX 5090 (Astral):
  • 2930Mhz max core clock
  • 1000Mhz core clock offset
  • +4400Mhz on VRAM (total 16000Mhz)
  • 400, 475 and 600W
• RTX 6000 PRO MaxQ (shunt modded, Watercooled):
  • 2930Mhz max core clock
  • 500Mhz core clock offset
  • +5700Mhz on VRAM (total 16000Mhz)
  • 300, 400 and 475W via undervolt + OC, 600W via TDP limit to 300W.
• RTX 6000 PRO WS:
  • Stock
  • 600W

For LLMs, used 500W for both GPUs, and for more reference I have this setup:

• RTX 6000 MaxQ (shunted) x2
• RTX 5090 x2
• RTX A6000
• NVIDIA A40
• RTX 4000 PRO SFF
• 192GB RAM DDR5 6000Mhz, Consumer AM5 + 9900X, PCIe 5.0 switch

So first, the results for the Anima ones look like this:

GPU	Power	Notes	Core Clock	Time	vs 5090 at 600W
RTX 6000 PRO MaxQ	600W	Shunt + watercooled (TDP)	2442 Mhz	32.7s	+12.8%
RTX 6000 PRO MaxQ	475W	Shunt + watercooled (UV+OC)	2160 Mhz	35.3s	+5.9%
RTX 6000 PRO WS	600W	Stock, rented	2340 Mhz	37.3s	+0.5%
RTX 5090	600W	UV+OC (baseline)	2520 Mhz	37.5s	-
RTX 6000 PRO MaxQ	400W	Shunt + watercooled (UV+OC)	1935 Mhz	38.3s	-2.1%
RTX 5090	475W	UV+OC	2160 Mhz	42.9s	-14.4%
RTX 6000 PRO MaxQ	300W	Watercooled (UV+OC)	1530 Mhz	46.6s	-24.3%
RTX 5090	400W	UV+OC	1860 Mhz	47.2s	-25.9%

Or, using the 5090 at 400W for baseline:

GPU	Power	Notes	Core Clock	Time	vs 5090 at 400W
RTX 6000 PRO MaxQ	600W	Shunt + watercooled (TDP)	2442 Mhz	32.7s	+30.7%
RTX 6000 PRO MaxQ	475W	Shunt + watercooled (UV+OC)	2160 Mhz	35.3s	+25.2%
RTX 6000 PRO WS	600W	Stock, rented	2340 Mhz	37.3s	+21%
RTX 5090	600W	UV+OC	2520 Mhz	37.5s	+20.6%
RTX 6000 PRO MaxQ	400W	Shunt + watercooled (UV+OC)	1935 Mhz	38.3s	+18.9%
RTX 5090	475W	UV+OC	2160 Mhz	42.9s	+9.1%
RTX 6000 PRO MaxQ	300W	Watercooled (UV+OC)	1530 Mhz	46.6s	+1.3%
RTX 5090	400W	UV+OC (Baseline)	1860 Mhz	47.2s	-

And then looking it from a efficiency perspective:

GPU	Power	Notes	Energy/batch	Time	vs MaxQ at 300W (higher the %, worse efficiency)
RTX 6000 PRO MaxQ	300W	Watercooled (UV+OC)	13.98 kJ	46.6s	-
RTX 6000 PRO MaxQ	400W	Shunt + WC (UV+OC)	15.32 kJ	38.3s	+9.6%
RTX 6000 PRO MaxQ	475W	Shunt + WC (UV+OC)	16.77 kJ	35.3s	+19.9%
RTX 5090	400W	UV+OC	18.88 kJ	47.2s	+35.1%
RTX 6000 PRO MaxQ	600W	Shunt + watercooled (UV+OC)	19.62 kJ	32.7s	+40.3%
RTX 5090	475W	UV+OC	20.38 kJ	42.9s	+45.8%
RTX 6000 PRO WS	600W	Stock, rented	22.38 kJ	37.3s	+60.1%
RTX 5090	600W	UV+OC	22.50 kJ	37.5s	+60.9%

And for the LLMs prompt processing ones, it look like this (remember all at 500W, but it uses way less, basically it reaches 2930Mhz on both GPUs:

Model	GPU	t/s PP	vs 5090
Kimi 2.5 IQ3_M (80GB offload)	RTX 6000 PRO MaxQ	548.08	+16.3%
Kimi 2.5 IQ3_M (80GB offload)	RTX 5090	471.40	-
GLM 5.1 IQ4_NL (70GB offload)	RTX 6000 PRO MaxQ	658.35	+14.5%
GLM 5.1 IQ4_NL (70GB offload)	RTX 5090	574.98	-

So as can you see, we have these points:

• It really seems the MaxQ are binned for higher clocks, I guess it makes sense, so they don't lose much performance at low power.
• Now after a shunt, the sweet spot seems to be 475W on a mix between of performance and power. Most efficient one, and it makes sense, is 300W, as the card comes from the factory.
• 5090 seems to place quite behind, more than I would expect. Take in mind this is a "good" bin, which can do high clocks at low power.
• On LLMs, since it is not power limited, it is basically all what the core can give and just the difference of more CUDA cores, and when the active models are bigger, there is a bigger difference.
• At the same power on MaxQ shunt vs 5090:
  • 400W: MaxQ is 23% faster.
  • 475W: MaxQ is 21% faster.
  • 600W: MaxQ is 15% faster.

Why you may ask? First, because I suspected MaxQ had better bins I expected, and indeed they were. It makes sense to have good bins to clock higher at 300-325W, and also to be manageable by the stock cooler.

Having the same power at 475W on both 5090 and 6000 PRO MaxQ but the latter being more than 20% faster is not something I expected, but that is a great surprise.

Also, because I'm just crazy, I have shunted a lot of cards already (5090, 4090, 3090, A6000, etc). Not recommended of course except if you know what you're doing, and are ready to lose the warranty.

Any question is welcome!

Hello guys, hoping you're doing fine!

I'm continuing after this post some time ago, comparing stock MaxQ performance and such on Anima here.

This time, I shunt modded the 6000 PRO MaxQ, to use up to 2x amounts of power. These cards seems to be binned for high clocks and it is reflected after this.

R002 resistance on top of stock resistance, making the card thinks it pulls half of the power, thus reaching 600W max power.

(Note that you can also solder a R002 resistance on the empty pad and it would work the same)

I also did watercool them to manage the heat, with a Bykski block (this one) at 170USD each from Aliexpress and a GLZM 360mm AIO. So had to get the tubes, coolant and fittings.

Sorry for the finger marks

GLZM AIO

For reference, at 300W it maxes at about 45°C, and at 600W it maxes at about 60°C.

MaxQ running at 624W

I also rented on runpod, a 6000 PRO WS edition, which it's power limit ranges from 150W to 600W (yes, lower than the MaxQ)

Important note again: I did undervolt+overclock the 5090 and the 6000 PRO MaxQ. I can't modify the clocks or power on the rented GPUs on runpod.

So for this test, I ran these settings for the software for pytorch:

• Torch 2.14.0.dev20260612+cu132 for the 5090 and 6000 PRO MaxQ.
• Torch 2.13.0+cu132 stable for the 6000 PRO WS.
• Sageattention 2.1 (on commit e9b072f0fc2682f104abbda306af3d42fc33b969), self built on CUDA 13.3.
• Forge neo on commit 644450e8bf2df24f0ba87307604d0e9f4ae3a9f7
• Installed extensions for RTX Upscaling (https://github.com/Haoming02/sd-forge-nvidia-vfx) and for extra samplers (https://github.com/Panchovix/sd_forge_neo_extra_samplers)
• torch compile: max autotune no cudagraphs

I ran these settings for the samplers and steps:

Forge settings

On text:

• EXP Heun 2 x0 SDE for first 25 steps
• ER SDE for 10 hires pass steps
• Upscale by 1.5x
• 896x1088 resolution
• Batch size 4
• CFG 5
• Shift 3
• Denoise Strength: 0.2
• Upscaler: NVIDIA Ultra
• Seed: 50906000

Prompt used was:

Positive:

masterpiece, best quality, high quality, high resolution, absurdres, highres, very aesthetic, sfw,
u/isshiki \(ffmania7\),
1girl, solo, clothed,
aether foundation employee, pokemon, dark skin, black hair, short hair,
happy,
from above,
full body,
beige background

Negative:

worst quality, low quality, bad anatomy, (jpeg artifacts:0.8), watermark, sketch, no pupils

For LLMs, I ran llamacpp with a model offloaded to CPU, making the primary GPU the bottleneck when traversing the data, making it compute bound.

Models tested were (offloaded):

• Kimi K2 2.5 (IQ3_M)
• GLM 5.1 (IQ4_NL)

The LLM tests were only tested on my local machine, as testing on cloud via renting a GPU is not feasible or won't have accurate results.

For the hardware, I ran them headless, (with LACT), for Anima:

• RTX 5090 (Astral):
  • 2930Mhz max core clock
  • 1000Mhz core clock offset
  • +4400Mhz on VRAM (total 16000Mhz)
  • 400, 475 and 600W
• RTX 6000 PRO MaxQ (shunt modded, Watercooled):
  • 2930Mhz max core clock
  • 500Mhz core clock offset
  • +5700Mhz on VRAM (total 16000Mhz)
  • 300, 400 and 475W via undervolt + OC, 600W via TDP limit to 300W.
• RTX 6000 PRO WS:
  • Stock
  • 600W

For LLMs, used 500W for both GPUs, and for more reference I have this setup:

• RTX 6000 MaxQ (shunted) x2
• RTX 5090 x2
• RTX A6000
• NVIDIA A40
• RTX 4000 PRO SFF
• 192GB RAM DDR5 6000Mhz, Consumer AM5 + 9900X, PCIe 5.0 switch

So first, the results for the Anima ones look like this:

GPU	Power	Notes	Core Clock	Time	vs 5090 at 600W
RTX 6000 PRO MaxQ	600W	Shunt + watercooled (TDP)	2442 Mhz	32.7s	+12.8%
RTX 6000 PRO MaxQ	475W	Shunt + watercooled (UV+OC)	2160 Mhz	35.3s	+5.9%
RTX 6000 PRO WS	600W	Stock, rented	2340 Mhz	37.3s	+0.5%
RTX 5090	600W	UV+OC (baseline)	2520 Mhz	37.5s	-
RTX 6000 PRO MaxQ	400W	Shunt + watercooled (UV+OC)	1935 Mhz	38.3s	-2.1%
RTX 5090	475W	UV+OC	2160 Mhz	42.9s	-14.4%
RTX 6000 PRO MaxQ	300W	Watercooled (UV+OC)	1530 Mhz	46.6s	-24.3%
RTX 5090	400W	UV+OC	1860 Mhz	47.2s	-25.9%

Or, using the 5090 at 400W for baseline:

GPU	Power	Notes	Core Clock	Time	vs 5090 at 400W
RTX 6000 PRO MaxQ	600W	Shunt + watercooled (TDP)	2442 Mhz	32.7s	+30.7%
RTX 6000 PRO MaxQ	475W	Shunt + watercooled (UV+OC)	2160 Mhz	35.3s	+25.2%
RTX 6000 PRO WS	600W	Stock, rented	2340 Mhz	37.3s	+21%
RTX 5090	600W	UV+OC	2520 Mhz	37.5s	+20.6%
RTX 6000 PRO MaxQ	400W	Shunt + watercooled (UV+OC)	1935 Mhz	38.3s	+18.9%
RTX 5090	475W	UV+OC	2160 Mhz	42.9s	+9.1%
RTX 6000 PRO MaxQ	300W	Watercooled (UV+OC)	1530 Mhz	46.6s	+1.3%
RTX 5090	400W	UV+OC (Baseline)	1860 Mhz	47.2s	-

And then looking it from a efficiency perspective:

GPU	Power	Notes	Energy/batch	Time	vs MaxQ at 300W (higher the %, worse efficiency)
RTX 6000 PRO MaxQ	300W	Watercooled (UV+OC)	13.98 kJ	46.6s	-
RTX 6000 PRO MaxQ	400W	Shunt + WC (UV+OC)	15.32 kJ	38.3s	+9.6%
RTX 6000 PRO MaxQ	475W	Shunt + WC (UV+OC)	16.77 kJ	35.3s	+19.9%
RTX 5090	400W	UV+OC	18.88 kJ	47.2s	+35.1%
RTX 6000 PRO MaxQ	600W	Shunt + watercooled (UV+OC)	19.62 kJ	32.7s	+40.3%
RTX 5090	475W	UV+OC	20.38 kJ	42.9s	+45.8%
RTX 6000 PRO WS	600W	Stock, rented	22.38 kJ	37.3s	+60.1%
RTX 5090	600W	UV+OC	22.50 kJ	37.5s	+60.9%

And for the LLMs prompt processing ones, it look like this (remember all at 500W, but it uses way less, basically it reaches 2930Mhz on both GPUs:

Model	GPU	t/s PP	vs 5090
Kimi 2.5 IQ3_M (80GB offload)	RTX 6000 PRO MaxQ	548.08	+16.3%
Kimi 2.5 IQ3_M (80GB offload)	RTX 5090	471.40	-
GLM 5.1 IQ4_NL (70GB offload)	RTX 6000 PRO MaxQ	658.35	+14.5%
GLM 5.1 IQ4_NL (70GB offload)	RTX 5090	574.98	-

So as can you see, we have these points:

• It really seems the MaxQ are binned for higher clocks, I guess it makes sense, so they don't lose much performance at low power.
• Now after a shunt, the sweet spot seems to be 475W on a mix between of performance and power. Most efficient one, and it makes sense, is 300W, as the card comes from the factory.
• 5090 seems to place quite behind, more than I would expect. Take in mind this is a "good" bin, which can do high clocks at low power.
• On LLMs, since it is not power limited, it is basically all what the core can give and just the difference of more CUDA cores, and when the active models are bigger, there is a bigger difference.
• At the same power on MaxQ shunt vs 5090:
  • 400W: MaxQ is 23% faster.
  • 475W: MaxQ is 21% faster.
  • 600W: MaxQ is 15% faster.

Why you may ask? First, because I suspected MaxQ had better bins I expected, and indeed they were. It makes sense to have good bins to clock higher at 300-325W, and also to be manageable by the stock cooler.

Having the same power at 475W on both 5090 and 6000 PRO MaxQ but the latter being more than 20% faster is not something I expected, but that is a great surprise.

Also, because I'm just crazy, I have shunted a lot of cards already (5090, 4090, 3090, A6000, etc). Not recommended of course except if you know what you're doing, and are ready to lose the warranty.

Any question is welcome!