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Building RTX 6000 PRO GPU Server #GPUServer #RTX6000 #TechInnovation #DataCenter #HighPerformance #ServerBuild #AIHardware #CloudComputing #InterServer #TechSolutions

InterServer

59,636 subscribers

98,662 görüntüleme • 4 ay önce •via X (Twitter)

#GPUServer #RTX6000 #TechInnovation #DataCenter #HighPerformance #ServerBuild #AIHardware #CloudComputing #InterServer #TechSolutions

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27 Yorum

Ufuoma Desmond profil fotoğrafı

Ufuoma Desmond4 ay önce

You guys are a disgrace. I can't upload anything to my hosting and I though it was the WordPress installation I contact your Customer Support and I was told that there is no problem and I need developers figure it out. What kind of hosting company hires incompetent staff?

CZ Calls profil fotoğrafı

CZ Calls4 ay önce

Development speed is impressive let’s reach out 🔥

ĐếVương | Lowkey profil fotoğrafı

ĐếVương | Lowkey2 ay önce

mấy con rtx 6000 pro này nhìn ngon thiệt, hồi xưa mơ build mà giờ chỉ dám chơi con card đồ họa có quạt nhỏ hơn quạt bàn 😅 build ngon nha bác

Jay profil fotoğrafı

Jay3 ay önce

I’m not able to change the root password of my VPS…. Being waiting for an hour Oh GOD🤦🏻‍♂️

Jay profil fotoğrafı

Jay3 ay önce

@interserver help me change my root password Been waiting for more than an hour 🤦🏻‍♂️

الأمــيـرَةُ_𝑨𝒍_𝑨𝒎𝒊𝒓𝒂𝒉 profil fotoğrafı

الأمــيـرَةُ_𝑨𝒍_𝑨𝒎𝒊𝒓𝒂𝒉3 ay önce

Send me a private message

Bwire foundation profil fotoğrafı

Bwire foundation3 ay önce

We are kindly requesting for your support brother and sister 🙏

BobVoyage (💙,🧡) | ⛽ profil fotoğrafı

BobVoyage (💙,🧡) | ⛽3 ay önce

Impressive setup! Do you share benchmarks from your builds regularly? 🔧💡

Victoria Blake profil fotoğrafı

Victoria Blake2 ay önce

Building high-performance AI infrastructure is key to powering the next generation of innovation. 🚀 We'd love to collaborate and help showcase InterServer's GPU solutions to a broader AI and developer audience. Looking forward to connecting! 🤝

Ummi profil fotoğrafı

Ummi2 ay önce

Nice

0xdefilink profil fotoğrafı

0xdefilink3 ay önce

i cant start a 💬 w u, can u try?

Aina Ai | Tools & Updates profil fotoğrafı

Aina Ai | Tools & Updates4 ay önce

Very nice

Ngọc My profil fotoğrafı

Ngọc My1 ay önce

The RTX 6000 PRO is a solid choice for AI workloads, should be a powerhouse for your server

Sysracks profil fotoğrafı

Sysracks1 ay önce

Soo cool 👍

مالكت 💃🏻تويتر 😱 profil fotoğrafı

مالكت 💃🏻تويتر 😱2 ay önce

تم

Jason Crypto profil fotoğrafı

Jason Crypto2 ay önce

This has huge potential. My DMs are open 🤝

NurturerGlow profil fotoğrafı

NurturerGlow3 ay önce

Me as @niyirora654 i like your contents alot

dody profil fotoğrafı

dody2 ay önce

هلا

Khon Bhai profil fotoğrafı

Khon Bhai1 ay önce

DM me for social media marketing at instagram

Priest profil fotoğrafı

Priest3 ay önce

Nice

Mr. 𝗡𝗔𝗹𝗼𝗻𝗲 🥀 profil fotoğrafı

Mr. 𝗡𝗔𝗹𝗼𝗻𝗲 🥀3 ay önce

"Powering the future of AI starts with the right infrastructure. 🔥 Wishing you a smooth build and top-tier performance! 🚀"

Kachis profil fotoğrafı

Kachis4 ay önce

This is amazing

Bit Nexus profil fotoğrafı

Bit Nexus2 ay önce

End today with grateful thoughts

Khing Sãffûł profil fotoğrafı

Khing Sãffûł1 ay önce

I've tried every means to very this thing but it's not working. How do you expect customers using local bank cards to get this done ? This is so poor

Thais Coelho profil fotoğrafı

Thais Coelho3 ay önce

can you start a 💬?

Lương Nguyễn profil fotoğrafı

Lương Nguyễn2 ay önce

G

Lee_1909 profil fotoğrafı

Lee_19092 ay önce

Wow, an RTX 6000 PRO server? That's serious horsepower for AI.

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Dee

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768GB of VRAM. Eight RTX PRO 6000 Blackwell cards. Liquid-cooled. 4U. We reviewed the Comino Grando and it is the most capable version of this platform yet by a wide margin. Comino @NVIDIA #AI #GPU #server

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Four Intel Arc Pro B70s in one box: 32GB of GDDR6 each, 128GB total, about $4,000 in GPUs. In our testing the quad setup more than doubles the DGX Spark and only trails a single RTX Pro 6000 that is much more expensive. Full review on the site. #IntelArc #GPUs #AIHardware Intel

StorageReview.com

67,572 görüntüleme • 2 ay önce

Quick video on how we wire up new racks. Yellow cables are for the public network. Orange Cables are for the private network. Every cable is labeled with the corresponding port number.

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InterServer

26,649 görüntüleme • 10 ay önce

GPU GIVEAWAY Buy a GPU × GTC 2026 = Give a GPU > RTX PRO 6000 Blackwell > 96GB VRAM • NVFP4 > ~$15K value > Brand new If this does well I’ll ask NVIDIA for more GPUs next time… maybe even DGX Sparks How to enter? Short clip here Full clip in the replies GO GO GO

Ahmad

36,697 görüntüleme • 7 ay önce

$RTX 3090 was never designed to be a server GPU. Yet someone just built a 4-GPU AI workstation around four of them. 4× RTX 3090 96GB VRAM 256GB ECC RAM AMD EPYC 7K62 2000W PSU 11 fans The interesting part isn't the performance. It's the memory. Four 24GB cards can be found for a fraction of what you'd pay for modern datacenter GPUs with similar total VRAM. The catch is obvious: 96GB doesn't behave like one 96GB GPU. You still have to deal with GPU-to-GPU communication, power and heat. But for local AI, this is exactly why the 3090 refuses to disappear. Would you build this today?$

RTX 3090 was never designed to be a server GPU. Yet someone just built a 4-GPU AI workstation around four of them. 4× RTX 3090 96GB VRAM 256GB ECC RAM AMD EPYC 7K62 2000W PSU 11 fans The interesting part isn't the performance. It's the memory. Four 24GB cards can be found for a fraction of what you'd pay for modern datacenter GPUs with similar total VRAM. The catch is obvious: 96GB doesn't behave like one 96GB GPU. You still have to deal with GPU-to-GPU communication, power and heat. But for local AI, this is exactly why the 3090 refuses to disappear. Would you build this today?

KyzoroX

36,552 görüntüleme • 27 gün önce

Scale your AI inference, graphics, and analytics workloads with the GPU power to get you there. Amazon EC2 G7 instances are now generally available—accelerated by @NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs, first on AWS.

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Amazon Web Services

1,960,506 görüntüleme • 3 ay önce

768GB of VRAM in one 4U server. That number sounds ridiculous until you remember it’s not one 768GB GPU. This Gigabyte G494-ZB4 packs: 8× RTX PRO 6000 Blackwell 768GB VRAM 2× EPYC 9554 1TB DDR5 ECC And that’s the part people often miss with multi-GPU systems. You can have almost 1TB of GPU memory, but the model still has to be split across 8 separate memory pools. So I think the next AI hardware race isn't just about how much memory you can put in a server. It's about how close that memory can behave to one giant pool. That’s a much harder problem to solve.

Sensitive content

768GB of VRAM in one 4U server. That number sounds ridiculous until you remember it’s not one 768GB GPU. This Gigabyte G494-ZB4 packs: 8× RTX PRO 6000 Blackwell 768GB VRAM 2× EPYC 9554 1TB DDR5 ECC And that’s the part people often miss with multi-GPU systems. You can have almost 1TB of GPU memory, but the model still has to be split across 8 separate memory pools. So I think the next AI hardware race isn't just about how much memory you can put in a server. It's about how close that memory can behave to one giant pool. That’s a much harder problem to solve.

KyzoroX

88,405 görüntüleme • 22 gün önce

Finally got my hands on the big one. Qwen3.5-122B-A10B — 122 billion parameters. Too big for any single consumer GPU. So I rented 4 of each... and then one professional card to see if brute force even matters. - 1x RTX PRO 6000 (96GB): 101.4 tok/s - 4x 5090 (128GB): 87.0 tok/s - 4x 4090 (96GB): 25.1 tok/s - 4x 3090 (96GB): 20.8 tok/s One single $8,500 card beat four RTX 5090s

Finally got my hands on the big one. Qwen3.5-122B-A10B — 122 billion parameters. Too big for any single consumer GPU. So I rented 4 of each... and then one professional card to see if brute force even matters. - 1x RTX PRO 6000 (96GB): 101.4 tok/s - 4x 5090 (128GB): 87.0 tok/s - 4x 4090 (96GB): 25.1 tok/s - 4x 3090 (96GB): 20.8 tok/s One single $8,500 card beat four RTX 5090s

stevibe

197,300 görüntüleme • 6 ay önce

MiniMax M2.7 is 230B params. Can you actually run it at home? I tested Unsloth's UD-IQ3_XXS (80GB) on 4 different rigs: 🟠 4x RTX 4090 (96GB): 71.52 tok/s, TTFT 1045ms 🟢 4x RTX 5090 (128GB): 120.54 tok/s, TTFT 725ms 🟡 1x RTX PRO 6000 (96GB): 118.74 tok/s, TTFT 765ms 🟣 DGX Spark (128GB) — 24.41 tok/s, TTFT 741ms Backend: llama.cpp. Context: 32k. Max tokens: 4096. I went with IQ3_XXS because it's the biggest quant that fits in 96GB VRAM while still leaving safe headroom for 32k context. Same quant across all four rigs, fairest comparison I could run. Now look at rough peak GPU power draw: 🟠 4x4090 → 1,800W peak (450W × 4) 🟢 4x5090 → 2,300W peak (575W × 4) 🟡 RTX PRO 6000 → 600W peak 🟣 DGX Spark → 240W peak (whole system) The RTX PRO 6000 is the quiet winner. One card, 96GB, matching a 4x5090 rig at roughly a quarter of the power and zero multi-GPU headaches. Best tokens-per-watt by a wide margin. DGX Spark is slow on generation but pulls the least power of any rig here, around 240W for the whole system. Prefill-friendly, memory-rich, wall-socket-friendly. And yes, plenty of people cap their cards. Even then, 4x 4090 or 4x 5090 still pulls well over 1,200W from the GPUs alone.

MiniMax M2.7 is 230B params. Can you actually run it at home? I tested Unsloth's UD-IQ3_XXS (80GB) on 4 different rigs: 🟠 4x RTX 4090 (96GB): 71.52 tok/s, TTFT 1045ms 🟢 4x RTX 5090 (128GB): 120.54 tok/s, TTFT 725ms 🟡 1x RTX PRO 6000 (96GB): 118.74 tok/s, TTFT 765ms 🟣 DGX Spark (128GB) — 24.41 tok/s, TTFT 741ms Backend: llama.cpp. Context: 32k. Max tokens: 4096. I went with IQ3_XXS because it's the biggest quant that fits in 96GB VRAM while still leaving safe headroom for 32k context. Same quant across all four rigs, fairest comparison I could run. Now look at rough peak GPU power draw: 🟠 4x4090 → 1,800W peak (450W × 4) 🟢 4x5090 → 2,300W peak (575W × 4) 🟡 RTX PRO 6000 → 600W peak 🟣 DGX Spark → 240W peak (whole system) The RTX PRO 6000 is the quiet winner. One card, 96GB, matching a 4x5090 rig at roughly a quarter of the power and zero multi-GPU headaches. Best tokens-per-watt by a wide margin. DGX Spark is slow on generation but pulls the least power of any rig here, around 240W for the whole system. Prefill-friendly, memory-rich, wall-socket-friendly. And yes, plenty of people cap their cards. Even then, 4x 4090 or 4x 5090 still pulls well over 1,200W from the GPUs alone.

stevibe

193,239 görüntüleme • 5 ay önce

Building my friend his dream pc 👀🫣 using the MSI Gaming USA RTX 5090 LIGHTNING Z 😍😍⚡️⚡️ what do you think?? 👀👀 those decals be popping! PC Parts List: CPU: Intel Core Ultra 7 265KF Motherboard: MSI MEG Z890 GODLIKE GPU: MSI RTX 5090 Lightning Z RAM: Corsair Dominator Titanium DDR5 SSD: MSI Spatium M480 Pro 2TB Cooler: MSI CoreLiquid P1 360 PSU: MSI AI1600T PCIE5 (1600W) Case: MSI MEG Maestro 700L PZ

Building my friend his dream pc 👀🫣 using the MSI Gaming USA RTX 5090 LIGHTNING Z 😍😍⚡️⚡️ what do you think?? 👀👀 those decals be popping! PC Parts List: CPU: Intel Core Ultra 7 265KF Motherboard: MSI MEG Z890 GODLIKE GPU: MSI RTX 5090 Lightning Z RAM: Corsair Dominator Titanium DDR5 SSD: MSI Spatium M480 Pro 2TB Cooler: MSI CoreLiquid P1 360 PSU: MSI AI1600T PCIE5 (1600W) Case: MSI MEG Maestro 700L PZ

Nay.Tesseract

22,354 görüntüleme • 6 ay önce

FOUR 600W GPUS. 384GB OF GDDR7. AND DELL MADE THE INSTALL LOOK EASIER THAN BUILDING A GAMING PC. this is a Dell PowerEdge XE7740 receiving four NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs. each card brings: 96GB GDDR7 ECC 24,064 CUDA cores 4 PFLOPS FP4 up to 600W but the most satisfying part is the cable management. every GPU power lead is already routed, labeled and held beside its assigned slot. drop in the card. lock the retention hardware. connect one 16-pin plug. no loose bundle hanging across the airflow path and no guessing which cable belongs where. the four-card build totals 384GB of GPU memory and 16 PFLOPS FP4. the 4U XE7740 supports up to eight of these GPUs, doubling that to 768GB and 32 PFLOPS FP4. honest line: the memory remains split between separate cards, and four GPUs can still pull up to 2.4kW. Dell made a rack-scale AI server this dense without turning the next GPU swap into cable surgery. bookmark & watch today ↓

FOUR 600W GPUS. 384GB OF GDDR7. AND DELL MADE THE INSTALL LOOK EASIER THAN BUILDING A GAMING PC. this is a Dell PowerEdge XE7740 receiving four NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs. each card brings: 96GB GDDR7 ECC 24,064 CUDA cores 4 PFLOPS FP4 up to 600W but the most satisfying part is the cable management. every GPU power lead is already routed, labeled and held beside its assigned slot. drop in the card. lock the retention hardware. connect one 16-pin plug. no loose bundle hanging across the airflow path and no guessing which cable belongs where. the four-card build totals 384GB of GPU memory and 16 PFLOPS FP4. the 4U XE7740 supports up to eight of these GPUs, doubling that to 768GB and 32 PFLOPS FP4. honest line: the memory remains split between separate cards, and four GPUs can still pull up to 2.4kW. Dell made a rack-scale AI server this dense without turning the next GPU swap into cable surgery. bookmark & watch today ↓

Grimmer

26,693 görüntüleme • 1 ay önce

Jak ze stacji roboczej HP - Z6 zrobić środowisko do vibe codingu? Przepis jest prosty - stacja robocza z 1x GPU (akurat moja posiada 2x Nvidia RTX PRO 6000 Blackewell Max-Q), lokalna instalacja vllm'a albo SGLang, najnowszy model Qwen3-Coder-30B-A3B-Instruct i żegnajcie limity, ograniczenia, płatności. 100% lokalnie, bez przekazywania danych, bezpiecznie. Zobaczmy, czy dzięki takiej stacji kilka osób jest w stanie pracować lokalnie. Oczywiście opencode. #HP #ZbyHP #HPIncPolska #StacjeRoboczeHP [płatna współpraca]

Jak ze stacji roboczej HP - Z6 zrobić środowisko do vibe codingu? Przepis jest prosty - stacja robocza z 1x GPU (akurat moja posiada 2x Nvidia RTX PRO 6000 Blackewell Max-Q), lokalna instalacja vllm'a albo SGLang, najnowszy model Qwen3-Coder-30B-A3B-Instruct i żegnajcie limity, ograniczenia, płatności. 100% lokalnie, bez przekazywania danych, bezpiecznie. Zobaczmy, czy dzięki takiej stacji kilka osób jest w stanie pracować lokalnie. Oczywiście opencode. #HP #ZbyHP #HPIncPolska #StacjeRoboczeHP [płatna współpraca]

Remek Kinas

21,533 görüntüleme • 7 ay önce

watch gemma 4 12b q8 dancing on a single rtx 3090 at 33 tokens a second average. google dropped this two days ago and it's the kind of thing that quietly moves the floor. a fully multimodal model, text image and audio in one net, 256k context, apache licensed, running entirely on one consumer gpu, no one metering your tokens. what you're watching is the whole loop live: the server streaming tokens top left, the gpu pegged bottom left, the answer landing on the right. all local, all mine. a year ago this needed someone else's datacenter. today it's a card you can buy. open source isn't catching up anymore, it's setting the pace. how fast does yours run?

watch gemma 4 12b q8 dancing on a single rtx 3090 at 33 tokens a second average. google dropped this two days ago and it's the kind of thing that quietly moves the floor. a fully multimodal model, text image and audio in one net, 256k context, apache licensed, running entirely on one consumer gpu, no one metering your tokens. what you're watching is the whole loop live: the server streaming tokens top left, the gpu pegged bottom left, the answer landing on the right. all local, all mine. a year ago this needed someone else's datacenter. today it's a card you can buy. open source isn't catching up anymore, it's setting the pace. how fast does yours run?

Sudo su

36,614 görüntüleme • 4 ay önce

384GB of VRAM. On your desk. Not in a datacenter. Autonomous, the company behind SmartDesk, just open sourced complete build guides for a personal AI computer that runs open models on hardware no one can switch off. It's called Autonomous Computer. Three configurations, one philosophy: a model you rent can be cut off overnight. A model running in your own house can't. → Home build: 2x RTX 5090 workstation → Team build: 4x RTX PRO 6000 Blackwell, 384GB VRAM → On-prem business build: 8x RTX 4090/5090, up to 256GB VRAM Every config ships with the full bill of materials, 3D printable and CNC housing files, wiring diagrams, BIOS tuning, and assembly photos. Software side covers OS setup, NVIDIA drivers, and serving open models through Ollama, vLLM, and llama.cpp. Fork it. Change it. Build it. Sell it. MIT License. 100% Opensource. Repo:

384GB of VRAM. On your desk. Not in a datacenter. Autonomous, the company behind SmartDesk, just open sourced complete build guides for a personal AI computer that runs open models on hardware no one can switch off. It's called Autonomous Computer. Three configurations, one philosophy: a model you rent can be cut off overnight. A model running in your own house can't. → Home build: 2x RTX 5090 workstation → Team build: 4x RTX PRO 6000 Blackwell, 384GB VRAM → On-prem business build: 8x RTX 4090/5090, up to 256GB VRAM Every config ships with the full bill of materials, 3D printable and CNC housing files, wiring diagrams, BIOS tuning, and assembly photos. Software side covers OS setup, NVIDIA drivers, and serving open models through Ollama, vLLM, and llama.cpp. Fork it. Change it. Build it. Sell it. MIT License. 100% Opensource. Repo:

Harman

48,089 görüntüleme • 2 ay önce

Timelapse #181 (11.1 hrs) - assembled a fair bit of the 4x RTX Pro 6000 Blackwell server build live on stream - bottlenecked debugging motherboard post codes and waiting on multiple multimeter deliveries - ended up doing a dozen component swaps to isolate the faults - drove for the first time in 4 years to hit the gym and grab 99% isopropyl to clean contacts, then resumed stream - crashed out with the entire room a total mess - exhausting day of hardware troubleshooting, but deeply fulfilling

Timelapse #181 (11.1 hrs) - assembled a fair bit of the 4x RTX Pro 6000 Blackwell server build live on stream - bottlenecked debugging motherboard post codes and waiting on multiple multimeter deliveries - ended up doing a dozen component swaps to isolate the faults - drove for the first time in 4 years to hit the gym and grab 99% isopropyl to clean contacts, then resumed stream - crashed out with the entire room a total mess - exhausting day of hardware troubleshooting, but deeply fulfilling

Elliot Arledge

10,914 görüntüleme • 26 gün önce