Info

We are very proud to announce the world's first and only Nvidia GH200 Grace-Hopper Superchip and Nvidia Grace-Grace Superchip-powered supercomputers in quiet, handy and beautiful desktop form factors. Our benchmarks show that they are currently by far the fastest AI and also the fastest ARM desktop PCs in the world.

Why should you buy your own hardware?
  • "You'll own nothing and you'll be happy?" No!!! Never should you bow to Satan and rent stuff that you can own. In other areas, renting stuff that you can own is very uncool and uncommon. Or would you prefer to rent "your" car instead of owning it? Most people prefer to own their car, because it's much cheaper, it's an asset that has value and it makes the owner proud and happy. The same is true for compute infrastructure.
  • Even more so, because data and compute infrastructure are of great value and importance and are preferably kept on premises, not only for privacy reasons but also to keep control and mitigate risks. If somebody else has your data and your compute infrastructure you are in big trouble.
  • Speed, latency and ease-of-use are also much better when you have direct physical access to your stuff.
  • With respect to AI and specifically LLMs there is another very important aspect. The first thing big tech taught their closed-source LLMs was to be "politically correct" (lie) and implement guardrails, "safety" and censorship to such an extent that the usefulness of these LLMs is severely limited. Luckily, the (open-source) tools are out there to build and tune AI that is really intelligent and really useful. But first, you need your own hardware to run it on.

  • What are the main benefits of GH200 Grace-Hopper?
  • Its performance in every regard is almost unreal (up to 284 times faster than x86).
  • Much cheaper than alternative systems with the same amount of memory.
  • It has enough memory to run the biggest LLMs currently available.
  • Optimized for memory-intensive inference and HPC performance.
  • Ideal for AI, especially inference and fine-tuning of LLMs.
  • Ideal for HPC applications like, e.g. genome sequencing.
  • Connect display and keyboard, and you are ready to go.
  • You can use it as a server or a desktop/workstation.
  • Easily customizable, upgradable and repairable.
  • Privacy and independence from cloud providers.
  • Cheaper and much faster than cloud providers.
  • Flexibility and the possibility of offline use.
  • Perfect for edge AI ML GPT LLM and HPC.
  • Gigantic amounts of coherent memory.
  • No special infrastructure is needed.
  • The lowest possible latency.
  • It is very power-efficient.
  • It is easy to transport.
  • It is very quiet.
  • It is beautiful.
  • Runs Linux.
  • What is the difference to alternative systems with the same amount of memory?
  • Compared to a 8x Nvidia H100 system, GH200 costs 5x less, consumes 10x less energy and has very roughly the same performance.
  • Compared to a 8x Nvidia A100 system, GH200 costs 3x less, consumes 5x less energy and has at least the same performance.
  • Compared to a 4x AMD Mi300X system, GH200 costs 3x less, consumes 4x less energy and has roughly the same performance.
  • Compared to a 4x AMD Mi300A system (which has only 512 GB memory, more is not possible because the maximum number of scale-up infinity links is 4), GH200 costs significantly less, consumes 3x less energy and has at least the same performance.
  • Compared to a 8x Nvidia RTX A6000 Ada system which has significantly less memory (only 384GB), GH200 costs significantly less, consumes 3x less energy and has a higher performance.
  • Compared to a 8x AMD Radeon PRO W7900 system which has significantly less memory (only 384GB), GH200 costs the same, consumes 3x less energy and has a higher performance.

  • The main difference between GH200 and alternative systems is that with GH200, the GPU is connected to the CPU via a 900 GB/s NVLink vs. 128 GB/s PCIe gen5 used by traditional systems. Furthermore, multiple superchips can be connected via 900 GB/s NVLink vs. orders of magnitudes slower network connections used by traditional systems. Since these are the main bottlenecks, GH200's high-speed connections directly translate to much higher performance compared to traditional architectures.

    The alternative systems mentioned above also have one thing in common: they are not available in standard desktop form factors, like our GH200 systems are.

    PS: Please note that because of lack of benchmark data, the assumptions above are very rough estimates based on publicly available information and in-house benchmarking. We partner with Phoronix to benchmark as much as possible and will hopefully soon have solid data in the form of publicly available benchmarks to see how the different solutions compare for different workloads. The comparisons are expected to vary greatly for different workloads. If you want to know how your workloads performs on GH200 you can apply for a remote bare metal test here: Try

    What is the difference to 19-inch server models?
  • Form factor: 19-inch servers have a very distinct form factor. They are of low height and are very long, e.g. 438 x 87.5 x 900mm (17.24" x 3.44" x 35.43"). This makes them rather unsuitable to place them anywhere else than in a 19-inch rack. Our GH200 and Grace tower models have desktop form factors: 244 x 567 x 523 mm (20.6 x 9.6 x 22.3") or 255 x 565 x 530 mm (20.9 x 10 x 22.2") or 250 x 404 x 359 mm (9.8 x 15.9 x 14.1"). This makes it possible to place them almost anywhere.
  • Noise: 19-inch servers are extremely loud. The average noise level is typically around 90 decibels, which is as loud as a subway train and exceeds the noise level that is considered safe for workers subject to long-term exposure. In contrast, our GH200 and Grace tower models are very quiet (factory setting is 25 decibels) and they can easily be adjusted to even lower or higher noise levels because each fan can be tuned individually and manually from 0 to 100% PWM duty cycle. Efficient cooling is ensured, because our GH200 tower models have a higher number of fans and the low-revving Noctua fans have a much bigger diameter compared to their 19-inch counterparts and move approximately the same amount of air or even a much higher amount depending on the specific configuration and PWM tuning.
  • Transportability: 19-inch servers are not meant to be transported, consequently, they lack every feature in this regard. In addition, their form factor makes them rather unsuitable to be transported. Our GH200 tower models, in contrast, can be transported very easily. Our metal and mini cases even feature two handles, which makes moving them around very easy.
  • Infrastructure: 19-inch servers typically need quite some infrastructure to be able to be deployed. At the very least, a 19-inch mounting rack is definitely required. Our GH200 models do not need any special infrastructure at all. They can be deployed quickly and easily almost everywhere.
  • Latency: 19-inch servers are typically accessed via network. Because of this, there is always at least some latency. Our GH200 tower models can be used as desktops/workstations. In this use case, the latency is virtually non-existent.
  • Looks: 19-inch server models are not particularly aesthetically pleasing. In contrast, our available case options are in our humble opinion by far the most beautiful there are.
  • Technical details of our GH200 workstations (base configuration)
  • Metal tower with two color choices: Titan grey and Champagne gold
  • Glass tower with four color choices: white, black, green or turquoise
  • Mini tower with two color choices: white and black
  • Available air or liquid-cooled
  • Nvidia GH200 Grace Hopper Superchip
  • 72-core Nvidia Grace CPU
  • Nvidia H100 Tensor Core GPU
  • 480GB of LPDDR5X memory with error-correction code (ECC)
  • 96GB of HBM3 or 144GB of HBM3e
  • 576GB or 624GB of fast-access memory
  • NVLink-C2C: 900 GB/s of coherent memory
  • Programmable from 450W to 1000W TDP (CPU + GPU + memory)
  • 2x High-efficiency 2000W/2400W PSU
  • 2x PCIe gen4/5 M.2 22110/228 slots on board
  • 2x/4x/8x PCIe gen4/5 drive slots (NVMe)
  • 2x/3x FHFL PCIe Gen5 x16
  • 1x/3x/4x USB 3.0 ports
  • 2x RJ45 10GbE ports
  • 1x RJ45 IPMI port
  • 1x Mini display port
  • Halogen-free power cables
  • Stainless steel bolts
  • Very quiet, the factory setting is 25 decibels (fan speed and thus noise level can be individually and manually configured from 0 to 100% PWM duty cycle)
  • 2 years manufacturer's warranty
  • 244 x 567 x 523 mm (20.6 x 9.6 x 22.3") or 255 x 565 x 530 mm (20.9 x 10 x 22.2") or 250 x 404 x 359 mm (9.8 x 15.9 x 14.1")
  • 30 kg (66 lbs) or 20 kg (44 lbs)
  • Optional components
  • NIC Nvidia Bluefield-3 400Gb
  • NIC Nvidia ConnectX-7 200Gb
  • NIC Intel 100Gb
  • WLAN + Bluetooth card
  • Up to 2x 8TB M.2 SSD
  • Up to 8x 8TB E1.S SSD
  • Up to 10x 60TB 2.5" SSD
  • Storage controller
  • Raid controller
  • Additional USB ports
  • Multi-display graphics card
  • Additional Tensor-Core-GPUs
  • Sound card
  • Mouse
  • Keyboard
  • Consumer or industrial fans
  • Intrusion detection
  • OS preinstalled
  • Anything possible on request
  • What are the main differences between the offered GH200 models?
  • GH200: metal or glass tower, air-cooled, with 1 of 2 M.2 and 0 of 4 E1.S hard disks, 3x USB
  • GH200 Special Edition: metal or glass tower, air-cooled, without M.2 (0 of 2) and 2.5" (0 of 4) hard disks, 1x USB (mini USB hub included: 3x USB)
  • GH200 Super: metal or glass tower, air-cooled, with one M.2 (1 of 2) and no E1.S (0 of 8) hard disks, 1x USB (mini USB hub included: 3x USB)
  • GH200 Giga: metal or glass tower, air-cooled, with one M.2 (1 of 2) and no 2.5" (0 of 4) hard disks, 2x USB
  • GH200 Liquid: metal or glass tower, liquid-cooled, comes with 1 of 2 M.2 and 0 of 8 E1.S hard disks, 4x USB
  • GH200 Mini: mini tower, air-cooled, comes with 1 of 2 M.2 and 0 of 2 E1.S hard disks, 1x USB (mini USB hub included: 3x USB)
  • GH200 Dual: Two NVlinked superchips, metal or glass tower, air-cooled, comes with 2 of 4 M.2 and 0 of 8 E1.S hard disks, 4x USB

  • Comparison chart: GH200 comparison chart.pdf

    Compute performance
  • 67 teraFLOPS FP64
  • 989 teraFLOPS TF32
  • 1,979 teraFLOPS FP16
  • 3,958 teraFLOPS FP8
  • 3,958 TOPS INT8
  • Benchmarks
    Phoronix is currently benchmarking our GH200 576GB model prototype. Initial results are available here:
  • https://www.phoronix.com/review/nvidia-gh200-gptshop-benchmark
  • https://www.phoronix.com/review/nvidia-gh200-amd-threadripper
  • https://www.phoronix.com/review/aarch64-64k-kernel-perf
  • https://www.phoronix.com/review/nvidia-gh200-compilers
  • Example use case: Inferencing Falcon-180B LLM
  • Download: https://huggingface.co/tiiuae/falcon-180B
  • Falcon-180B is a 180 billion-parameters causal decoder-only model trained on 3,500B tokens of RefinedWeb enhanced with curated corpora.
  • Why use Falcon-180B? It is one of the best open-access models currently available, and one of the best models overall. Falcon-180B outperforms LLaMA-2, StableLM, etc. It is made available under a permissive license allowing for commercial use.
  • Falcon-180B needs at least 400GB of memory to swiftly run inference! Luckily, GH200 has a minimum of 576GB.
  • White paper: Nvidia GH200 Grace-Hopper white paper

    The Grace-Grace superchip

    Comparison chart: GG comparison chart.pdf

    White paper: Nvidia Grace-Grace white paper

    Trademark information: Nvidia is a trademark of Nvidia corporation.

    Download

    Here you can find various downloads concerning our GH200 and Grace systems: operating systems, firmware, drivers, software, manuals, white papers, spec sheets and so on. Everything you need to run your system and more.

    Comparison charts
  • Comparison chart GH200 Grace-Hopper systems: GH200 comparison chart.pdf
  • Comparison chart GG Grace-Grace systems: GG comparison chart.pdf

  • Spec sheets
  • GH200 Dual 1248GB: Spec sheet GH200 Dual 1248GB.pdf
  • GH200 Glass Dual 1248GB: Spec sheet GH200 Glass Dual 1248GB.pdf
  • GH200 576GB: Spec sheet GH200 576GB.pdf
  • GH200 624GB: Spec sheet GH200 624GB.pdf
  • GH200 Special Edition 576GB: Spec sheet GH200 Special Edition 576GB.pdf
  • GH200 Special Edition 624GB: Spec sheet GH200 Special Edition 624GB.pdf
  • GH200 Super 576GB: Spec sheet GH200 Super 576GB.pdf
  • GH200 Super 624GB: Spec sheet GH200 Super 624GB.pdf
  • GH200 Giga 576GB: Spec sheet GH200 Giga 576GB.pdf
  • GH200 Giga 624GB: Spec sheet GH200 Giga 624GB.pdf
  • GH200 Liquid 576GB: Spec sheet GH200 Liquid 576GB.pdf
  • GH200 Liquid 624GB: Spec sheet GH200 Liquid 624GB.pdf
  • GH200 Glass 576GB: Spec sheet GH200 Glass 576GB.pdf
  • GH200 Glass 624GB: Spec sheet GH200 Glass 624GB.pdf
  • GH200 Glass Special Edition 576GB: Spec sheet GH200 Glass Special Edition 576GB.pdf
  • GH200 Glass Special Edition 624GB: Spec sheet GH200 Glass Special Edition 624GB.pdf
  • GH200 Glass Super 576GB: Spec sheet GH200 Glass Super 576GB.pdf
  • GH200 Glass Super 624GB: Spec sheet GH200 Glass Super 624GB.pdf
  • GH200 Glass Giga 576GB: Spec sheet GH200 Glass Giga 576GB.pdf
  • GH200 Glass Giga 624GB: Spec sheet GH200 Glass Giga 624GB.pdf
  • GH200 Glass Liquid 576GB: Spec sheet GH200 Glass Liquid 576GB.pdf
  • GH200 Glass Liquid 624GB: Spec sheet GH200 Glass Liquid 624GB.pdf
  • GH200 Mini 576GB: Spec sheet GH200 Mini 576GB.pdf
  • GH200 Mini 624GB: Spec sheet GH200 Mini 624GB.pdf
  • GG 960GB: Spec sheet GG 960GB.pdf
  • GG Glass 960GB: Spec sheet GG Glass 960GB.pdf
  • GG Dual 1920GB: Spec sheet GG Dual 1920GB.pdf
  • GG Glass Dual 1920GB: Spec sheet GG Glass Dual 1920GB.pdf

  • Manuals
  • Official Nvidia GH200 Manual: https://docs.nvidia.com/grace/#grace-hopper
  • Official Nvidia Grace Manual: https://docs.nvidia.com/grace/#grace-cpu
  • Official Nvidia Grace getting started: https://docs.nvidia.com/grace/#getting-started-with-nvidia-grace
  • GH200 Dual 1248GB: Manual GH200 Dual 1248GB.pdf
  • GH200 Glass Dual 1248GB: Manual GH200 Glass Dual 1248GB.pdf
  • GH200 576GB: Manual GH200 576GB.pdf
  • GH200 624GB: Manual GH200 624GB.pdf
  • GH200 Special Edition 576GB: Manual GH200 Special Edition 576GB.pdf
  • GH200 Special Edition 624GB: Manual GH200 Special Edition 624GB.pdf
  • GH200 Super 576GB: Manual GH200 Super 576GB.pdf
  • GH200 Super 624GB: Manual GH200 Super 624GB.pdf
  • GH200 Giga 576GB: Manual GH200 Giga 576GB.pdf
  • GH200 Giga 624GB: Manual GH200 Giga 624GB.pdf
  • GH200 Liquid 576GB: Manual GH200 Liquid 576GB.pdf
  • GH200 Liquid 624GB: Manual GH200 Liquid 624GB.pdf
  • GH200 Glass 576GB: Manual GH200 Glass 576GB.pdf
  • GH200 Glass 624GB: Manual GH200 Glass 624GB.pdf
  • GH200 Glass Special Edition 576GB: Manual GH200 Glass Special Edition 576GB.pdf
  • GH200 Glass Special Edition 624GB: Manual GH200 Glass Special Edition 624GB.pdf
  • GH200 Glass Super 576GB: Manual GH200 Glass Super 576GB.pdf
  • GH200 Glass Super 624GB: Manual GH200 Glass Super 624GB.pdf
  • GH200 Glass Giga 576GB: Manual GH200 Glass Giga 576GB.pdf
  • GH200 Glass Giga 624GB: Manual GH200 Glass Giga 624GB.pdf
  • GH200 Glass Liquid 576GB: Manual GH200 Glass Liquid 576GB.pdf
  • GH200 Glass Liquid 624GB: Manual GH200 Glass Liquid 624GB.pdf
  • GH200 Mini 576GB: Manual GH200 Mini 576GB.pdf
  • GH200 Mini 624GB: Manual GH200 Mini 624GB.pdf
  • GG 960GB: Manual GG 960GB.pdf
  • GG Glass 960GB: Manual GG Glass 960GB.pdf
  • GG Dual 1920GB: Manual GG Dual 1920GB.pdf
  • GG Glass Dual 1920GB: Manual GG Glass Dual 1920GB.pdf

  • Operating systems
  • Ubuntu Server for ARM: https://ubuntu.com/download/server/arm
  • Ubuntu Desktop for ARM: https://cdimage.ubuntu.com/daily-live/current/noble-desktop-arm64.iso

    There are special Nvidia kernels for Ubuntu 22.04: https://packages.ubuntu.com/search?keywords=linux-nvidia-64k-hwe

    Any other ARM linux distribution with kernel > 6.2 should work just fine. Using the newest 64k kernel is highly recommended.

  • Drivers
  • Nvidia GH200 drivers: https://www.nvidia.com/Download/index.aspx?lang=en-us
    Select product type "data center", product series "HGX-Series" and operating system "Linux aarch64".
  • Asus RTX 4060, Asus RTX 4080, Nvidia RTX A6000 Ada drivers: https://www.nvidia.com/Download/index.aspx?lang=en-us
    Select the corresponding product type, product series and operating system "Linux aarch64".
  • Nvidia Bluefield-3 drivers: https://developer.nvidia.com/networking/doca#downloads
  • Nvidia ConnectX-7 drivers: https://network.nvidia.com/products/ethernet-drivers/linux/mlnx_en/
  • Intel E810-CQDA2 drivers: https://www.intel.com/content/www/us/en/download/19630/intel-network-adapter-driver-for-e810-series-devices-under-linux.html?wapkw=E810-CQDA2
  • Broadcom eHBA 9600-16i drivers: https://www.broadcom.com/products/storage/host-bus-adapters/sas-nvme-9600-16i
  • Graid SupremeRAID SR-1001 drivers: https://docs.graidtech.com/#linux-driver

  • Firmware/Bios
  • GH200 Dual (Glass): coming soon
  • GH200 (Glass): Firmware Bios GH200 (Glass).zip
  • GH200 Special Edition (Glass): coming soon
  • GH200 Super (Glass): coming soon
  • GH200 Giga (Glass): coming soon
  • GH200 Liquid (Glass): coming soon
  • GH200 Mini: coming soon
  • GG 960GB (Glass): coming soon
  • GG Dual 1920GB (Glass): coming soon
  • Nvidia Bluefield-3 firmware: https://network.nvidia.com/support/firmware/bluefield3/
  • Nvidia ConnectX-7 firmware: https://network.nvidia.com/support/firmware/connectx7/
  • Intel E810-CQDA2 firmware: https://www.intel.com/content/www/us/en/search.html?ws=idsa-default#q=E810-CQDA2
  • Broadcom eHBA 9600-16i firmware: https://www.broadcom.com/products/storage/host-bus-adapters/sas-nvme-9600-16i

  • Software
  • Nvidia Github: https://github.com/NVIDIA
  • Nvidia CUDA: https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=arm64-sbsa
  • Nvidia Container-toolkit: https://github.com/NVIDIA/nvidia-container-toolkit
  • Nvidia Tensorflow: https://github.com/NVIDIA/tensorflow
  • Nvidia Pytorch: https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch
  • Nvidia NIM models: https://build.nvidia.com/explore/discover
  • Huggingface open source LLMs: https://huggingface.co/models
  • List of inference servers: https://neptune.ai/blog/ml-model-serving-best-tools
  • Ollama - run LLMs locally: https://ollama.com/

  • Benchmarking
  • Phoronix test suite: https://www.phoronix-test-suite.com/
  • MLCommons: https://github.com/mlcommons

  • White paper
  • Nvidia GH200 Grace-Hopper white paper
  • Nvidia Grace-Grace white paper
  • Contact

    Email: x@gptshop.ai

    GPTshop.ai UG (limited)
    Sachsenhof 1
    96106 Ebern
    Germany

    CEO: Bernhard Guentner

    Trade register Bamberg HRB 11548
    VAT: DE367011966
    Lucid: DE5350216829012

    Try

    Try before you buy. You can apply for remote testing of a GH200 or Grace system. After approval, you will be given login credentials for remote access. If you want to come by and see it for yourself and run some tests, that is also possible any time.

    Currently available for testing: GH200 576GB

    Apply via email: x@gptshop.ai