With the release of the new Blackwell chip generation for the consumer GPU market, it was expected to see workstation versions of the GPU as well — versions intended to replace the A5000/A6000 series and priced lower than A100/H100-level GPUs. This did happen, but in the process, NVIDIA completely confused everyone by launching no fewer than three versions of the RTX PRO 6000 Blackwell in just six months. We at HOSTKEY joined the performance race with the release of the latest version — the RTX PRO 6000 Blackwell Server Edition — tested it thoroughly, and we have some results to share (and show). Try the server with NVIDIA RTX 6000 PRO 96 GB — for free!
Contact our sales team to learn about the test-drive conditions.*
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* - The GPU is provided for a free trial on an individual basis and is not available in all cases. Try the server with NVIDIA RTX 6000 PRO 96 GB — for free! Try the server with NVIDIA RTX 6000 PRO 96 GB — for free! Contact our sales team to learn about the test-drive conditions.* Reach out to us Reach out to us * - The GPU is provided for a free trial on an individual basis and is not available in all cases. What are you? If you look at the official GPU specifications on the Nvidia website, we see the following picture: official GPU specifications official GPU specifications We have three video card options that differ in form factor, cooling  system type, and maximum power consumption. At first glance, one might  assume that the middle version (Workstation Edition) should be the  fastest and likely the hottest, based on its power consumption. Let's  compare their specifications in more detail and contrast them with the  fastest RTX 5090D. Workstation Edition

Max-Q Workstation edition

Server Edition

RTX 5090



CUDA Parallel Processing cores

24064

24064

24064

21760



Single-Precision Performance (FP32)

125 TFLOPS

125 TFLOPS

120 TFLOPS

103 TFLOPS



RT Core Performance

380 TFLOPS

333 TFLOPS

355 TFLOPS

-



Memory Bandwidth

1792 GB/s

1792 GB/s

1597 GB/s

1792 GB/sec



GPU Memory

96 GB GDDR7 with ECC

96 GB GDDR7 with ECC

96 GB GDDR7 with ECC

32 GB GDDR7



Memory Interface

512-bit

512-bit

512-bit

512-bit



Power Consumption

Up to 600W (Configurable)

300W

600W

575W Workstation Edition

Max-Q Workstation edition

Server Edition

RTX 5090



CUDA Parallel Processing cores

24064

24064

24064

21760



Single-Precision Performance (FP32)

125 TFLOPS

125 TFLOPS

120 TFLOPS

103 TFLOPS



RT Core Performance

380 TFLOPS

333 TFLOPS

355 TFLOPS

-



Memory Bandwidth

1792 GB/s

1792 GB/s

1597 GB/s

1792 GB/sec



GPU Memory

96 GB GDDR7 with ECC

96 GB GDDR7 with ECC

96 GB GDDR7 with ECC

32 GB GDDR7



Memory Interface

512-bit

512-bit

512-bit

512-bit



Power Consumption

Up to 600W (Configurable)

300W

600W

575W Workstation Edition

Max-Q Workstation edition

Server Edition

RTX 5090 Workstation Edition Workstation Edition Max-Q Workstation edition Max-Q Workstation edition Server Edition Server Edition RTX 5090 RTX 5090 CUDA Parallel Processing cores

24064

24064

24064

21760 CUDA Parallel Processing cores CUDA Parallel Processing cores 24064 24064 24064 24064 24064 24064 21760 21760 Single-Precision Performance (FP32)

125 TFLOPS

125 TFLOPS

120 TFLOPS

103 TFLOPS Single-Precision Performance (FP32) Single-Precision Performance (FP32) 125 TFLOPS 125 TFLOPS 125 TFLOPS 125 TFLOPS 120 TFLOPS 120 TFLOPS 103 TFLOPS 103 TFLOPS RT Core Performance

380 TFLOPS

333 TFLOPS

355 TFLOPS

- RT Core Performance RT Core Performance 380 TFLOPS 380 TFLOPS 333 TFLOPS 333 TFLOPS 355 TFLOPS 355 TFLOPS - - Memory Bandwidth

1792 GB/s

1792 GB/s

1597 GB/s

1792 GB/sec Memory Bandwidth Memory Bandwidth 1792 GB/s 1792 GB/s 1792 GB/s 1792 GB/s 1597 GB/s 1597 GB/s 1792 GB/sec 1792 GB/sec GPU Memory

96 GB GDDR7 with ECC

96 GB GDDR7 with ECC

96 GB GDDR7 with ECC

32 GB GDDR7 GPU Memory GPU Memory 96 GB GDDR7 with ECC 96 GB GDDR7 with ECC 96 GB GDDR7 with ECC 96 GB GDDR7 with ECC 96 GB GDDR7 with ECC 96 GB GDDR7 with ECC 32 GB GDDR7 32 GB GDDR7 Memory Interface

512-bit

512-bit

512-bit

512-bit Memory Interface Memory Interface 512-bit 512-bit 512-bit 512-bit 512-bit 512-bit 512-bit 512-bit Power Consumption

Up to 600W (Configurable)

300W

600W

575W Power Consumption Power Consumption Up to 600W (Configurable) Up to 600W (Configurable) 300W 300W 600W 600W 575W 575W The GPU we tested (RTX 6000 Blackwell Server Edition) is  the weakest in the lineup (although one might expect the Server version  to be more powerful than the Workstation edition), yet it still  outperforms the consumer-grade RTX 5090 due to a higher core count on  the chip. Thanks to reduced clock speeds, the card's power consumption  remains within 300W, but it can be toggled into boost mode, where it  operates at frequencies close to those of the Workstation Edition. In  300W mode, the card runs cooler than the RTX 5090, but when boosted, it  surpasses the consumer version in performance. The main feature of the Server Edition is its passive  cooling, which utilizes the standard airflow of the server chassis.  Thanks to its compact size, it allows for the simultaneous placement of a  large number of GPUs in a row (photo from the exhibition). Assembling the Server We will test this GPU using the following configuration: Server platform from ASUS
AMD EPYC 9554 processor
768 GB DDR5 RAM
2 x 3.84 TB NVMe
1 x RTX 6000 PRO SERVER Server platform from ASUS AMD EPYC 9554 processor 768 GB DDR5 RAM 2 x 3.84 TB NVMe 1 x RTX 6000 PRO SERVER Technically, the platform supports up to 4 GPUs, but due to power  consumption limitations in the no-power-restriction mode, a maximum of  two RTX 6000 PRO SERVER GPUs can be installed. The issue arises because  the platform provides 4 power connectors per side, which are connected  to the card via an adapter. As shown in the photo, the case is equipped  with powerful fans on both sides and a specialized housing, ensuring  excellent airflow over the radiators and GPU components. Now, onto the tests We'll conduct the tests in two modes: running LLMs using  the Ollama + OpenWebUI setup and video generation with the free WAN2  model in ComfyUI. More precisely, we'll use our neural network  assistant, which employs multiple models for RAG (Retrieval-Augmented  Generation) and interacts with an external MCP server. The LLM under  test is Qwen3-14B, which requires approximately 14 GB of VRAM in 16K  context mode. Looking ahead, we can say that comparisons involving models  fully fitting into the GPU show a performance increase of around 15–20%  over the RTX 5090. Therefore, we'll present results relative to other  GPUs rather than using the RTX 5090 as a baseline. To start, we'll compare the previous generation A5000 with  the RTX 6000 PRO. The comparison will be conducted in low power  consumption mode, where the GPU actually consumes up to 450W (boost  mode), rather than the 300W maximum stated in the documentation. Recall  that the A5000 features 24 GB of GDDR6 VRAM. We'll ask our neural network assistant the following question: "Hi. How to install Nvidia drivers on Linux?" GPU

Response Speed, Tokens per Second

Response Speed, Tokens per Second

Response Speed, Tokens per Second



A5000 (Cold Boot)

47.3

2700

17



RTX 6000 PRO (Cold Boot)

103.5

8285

5



A5000 (Model Already Loaded to GPU)

48.2

2910

13



RTX 6000 PRO (Model Already Loaded to GPU)

107

11000

4 GPU

Response Speed, Tokens per Second

Response Speed, Tokens per Second

Response Speed, Tokens per Second



A5000 (Cold Boot)

47.3

2700

17



RTX 6000 PRO (Cold Boot)

103.5

8285

5



A5000 (Model Already Loaded to GPU)

48.2

2910

13



RTX 6000 PRO (Model Already Loaded to GPU)

107

11000

4 GPU

Response Speed, Tokens per Second

Response Speed, Tokens per Second

Response Speed, Tokens per Second GPU GPU Response Speed, Tokens per Second Response Speed, Tokens per Second Response Speed, Tokens per Second Response Speed, Tokens per Second Response Speed, Tokens per Second Response Speed, Tokens per Second A5000 (Cold Boot)

47.3

2700

17 A5000 (Cold Boot) A5000 (Cold Boot) 47.3 47.3 2700 2700 17 17 RTX 6000 PRO (Cold Boot)

103.5

8285

5 RTX 6000 PRO (Cold Boot) RTX 6000 PRO (Cold Boot) 103.5 103.5 8285 8285 5 5 A5000 (Model Already Loaded to GPU)

48.2

2910

13 A5000 (Model Already Loaded to GPU) A5000 (Model Already Loaded to GPU) 48.2 48.2 2910 2910 13 13 RTX 6000 PRO (Model Already Loaded to GPU)

107

11000

4 RTX 6000 PRO (Model Already Loaded to GPU) RTX 6000 PRO (Model Already Loaded to GPU) 107 107 11000 11000 4 4 As you can see, compared to the A5000, which is still in  use, the new GPU is over two times more powerful, and its response speed  (i.e., switching between models, searching, querying the MCP server,  processing, and generating responses) is more than three times faster. However, using the RTX 6000 PRO for such tasks is like cracking nuts  with a microscope. For comparison, let’s test the same workload on the  H100 in a "hot run" (with the model already loaded). The H100 has 3.5  times fewer CUDA cores, lower clock speeds, and theoretical performance  roughly 4 times lower in synthetic benchmarks compared to the RTX 6000  PRO. However, it benefits from a 4nm process node (vs. 5nm for the RTX  6000 PRO), 10 times greater memory bandwidth, and a more advanced memory  type. Despite this, our version of the H100 has 80 GB of memory,  compared to the H100’s 96 GB. GPU

Response Speed, Tokens per Second

Response Speed, Tokens per Second

Response Speed, Tokens per Second



H100 (Model Already Loaded to GPU)

60

2900

4



RTX 6000 PRO (Model Already Loaded to GPU)

107

11000

4 GPU

Response Speed, Tokens per Second

Response Speed, Tokens per Second

Response Speed, Tokens per Second



H100 (Model Already Loaded to GPU)

60

2900

4



RTX 6000 PRO (Model Already Loaded to GPU)

107

11000

4 GPU

Response Speed, Tokens per Second

Response Speed, Tokens per Second

Response Speed, Tokens per Second GPU GPU Response Speed, Tokens per Second Response Speed, Tokens per Second Response Speed, Tokens per Second Response Speed, Tokens per Second Response Speed, Tokens per Second Response Speed, Tokens per Second H100 (Model Already Loaded to GPU)

60

2900

4 H100 (Model Already Loaded to GPU) H100 (Model Already Loaded to GPU) 60 60 2900 2900 4 4 RTX 6000 PRO (Model Already Loaded to GPU)

107

11000

4 RTX 6000 PRO (Model Already Loaded to GPU) RTX 6000 PRO (Model Already Loaded to GPU) 107 107 11000 11000 4 4 Despite the RTX 6000 PRO’s nearly twofold advantage in  tokenization speed, the overall performance of both GPUs is on par. This  makes the RTX 6000 PRO an excellent replacement for the A100/H100 in  server inference workloads, considering that HBM3’s bandwidth during  data transfers lags behind GDDR7. However, for model training or  fine-tuning, the H100 excels due to its reduced power consumption,  hardware-level support via the Transformer Engine for models with  FP16/FP8 precision (the H100 supports only FP4), and its ability to  accelerate tasks when models are fully loaded into memory (with  bandwidth up to 3 TB/s). Putting the RTX 6000 PRO to Full Use Much more interesting is to test this GPU in another  resource-intensive task—specifically, video generation. For this, we'll  use a new model from Alibaba with open weights and install everything in  ComfyUI. Again, we've encountered a problem: CUDA 12.9 (and later  versions) and its compatibility with PyTorch. The solution, once again,  is to install from nightly builds until official support is available: pip install --pre --upgrade --no-cache-dir torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cu129 pip install --pre --upgrade --no-cache-dir torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cu129 The process involves using the video generation mode based on prompts (Wan 2.2 14B text to video), which operates as follows: A whimsical and humorous scene unfolds on a serene riverbank, where two hardworking beavers in bright yellow safety helmets and rugged orange overalls team up to haul a massive, gleaming server rack toward their meticulously built beaver lodge. The lodge, constructed from logs and stones, features a bold, modern sign reading "HOSTKEY" in bold, tech-inspired typography. The beavers’ determined expressions and the server rack’s glowing lights create a surreal blend of nature and technology. The river sparkles in the sunlight, and the lodge’s entrance is framed by lush greenery, emphasizing the harmony between the beavers’ natural habitat and their unexpected tech-savvy mission. The scene is vibrant, detailed, and filled with playful energy, blending the charm of wildlife with the precision of data infrastructure. Perfect for a lighthearted, tech-themed animation or meme. A whimsical and humorous scene unfolds on a serene riverbank, where two hardworking beavers in bright yellow safety helmets and rugged orange overalls team up to haul a massive, gleaming server rack toward their meticulously built beaver lodge. The lodge, constructed from logs and stones, features a bold, modern sign reading "HOSTKEY" in bold, tech-inspired typography. The beavers’ determined expressions and the server rack’s glowing lights create a surreal blend of nature and technology. The river sparkles in the sunlight, and the lodge’s entrance is framed by lush greenery, emphasizing the harmony between the beavers’ natural habitat and their unexpected tech-savvy mission. The scene is vibrant, detailed, and filled with playful energy, blending the charm of wildlife with the precision of data infrastructure. Perfect for a lighthearted, tech-themed animation or meme. Launching the process takes approximately 40 minutes.  Memory usage and power consumption during peak performance are visible  in the screenshot below. The maximum temperature never exceeded 83  degrees. The generation is set to 720p/24, as the model is optimized for  this resolution. Setting it to 1080p or increasing the frame rate may  cause the GPU to freeze or significantly extend the generation time  beyond two hours (we didn’t wait longer, as the process became stuck at  60%). If we were to use the WAN 2.2 5B model instead, generating a similar video (5 seconds, 24 frames) takes just 160 seconds. Enhancing Power As previously mentioned, the GPU features a power  consumption mode switch. While this setting didn’t significantly benefit  the models, switching to a 600-watt power mode already yields improved  results. According to nvidia-smi readings, we managed to extract an  additional five watts of performance from the GPU. However, in this  mode, temperatures may spike up to 90 degrees. On average, power consumption in both modes during generation remains within the 200–250 watt range. As evident, increasing the maximum power consumption  accelerates the generation by 25%, reducing it to an average of 30  minutes. However, this comes at the cost of significantly higher chip  and component temperatures. For tasks requiring prolonged GPU operation  under heavy load, it’s advisable to keep the system in low-power  consumption mode to avoid thermal stress. Conclusion The GPU has proven to be impressive. It is far more stable  than the consumer-grade 5090, lacks the dust-prone fans often found on  consumer models, features superior memory with parity control, and  offers higher clock speeds. Compared to the H100, it is four times more affordable  while delivering comparable (and in some cases even better) performance  for tasks unrelated to deep neural network training. Inference, graphics  processing, and video handling are significantly faster than in  previous generations, and the new CUDA 13 alongside the latest 580  driver version further boosted performance. A key limitation is the lack of drivers (as of the time of  writing) for the Server Edition of Windows. While drivers are available  for the Workstation Edition, installation attempts result in a message  stating that the GPU is not detected. This issue does not occur in  Linux, where we successfully tested the card on both Ubuntu 22.04 and  24.04. However, the drivers required the linux kernel version 6+ and GCC  12 for compilation. Try the server with NVIDIA RTX 6000 PRO 96 GB — for free!
Contact our sales team to learn about the test-drive conditions.*
Reach out to us
* - The GPU is provided for a free trial on an individual basis and is not available in all cases. Try the server with NVIDIA RTX 6000 PRO 96 GB — for free! Try the server with NVIDIA RTX 6000 PRO 96 GB — for free! Contact our sales team to learn about the test-drive conditions.* Reach out to us Reach out to us * - The GPU is provided for a free trial on an individual basis and is not available in all cases.

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NVIDIA RTX 6000 Blackwell Server Edition: Tests, Benchmarks & Comparison

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