Can't afford Nvidia's expensive AI accelerators? Then consider this 10.8Kw server cluster with 32 Intel GPUs and 768GB VRAM

Date:
Sun, 12 Oct 2025 13:02:00 +0000

Description:
Sparkle unveils a 10.8Kw GPU cluster with 32 Intel GPUs and 768GB VRAM to provide affordable compute power for AI workloads.

FULL STORY ======================================================================Sparkles
dense PCIe 5.0 design offers lower-cost entry into AI and data research Up
to 32 Intel GPUs deliver 768GB VRAM for scalable AI computing 10,800W redundant power system and advanced cooling enable continuous heavy workloads

Taiwanese graphics card manufacturer Sparkle has taken the wraps off its new dense, scalable GPU server which could offer an alternative to costly AI accelerator systems like Nvidias H100, H200, and B200 data center GPUs.

The C741-6U-Dual 16P is designed to house up to 16 Arc Pro B60 Dual graphics cards, providing a total of 32 Intel GPUs and as much as 768GB of combined VRAM.

Each Arc Pro B60 Dual features two Battlemage BMG-G21 GPUs, and when fully equipped, the system will deliver a whopping 81,920 GPU cores. Advanced cooling

The server supports both 24GB and 48GB GPU models, paired with 4th or 5th Generation Intel Xeon Scalable processors.

It uses Intels C741 chipset and supports up to 32 DDR5 memory slots, allowing 256GB per module for intensive workloads.

Sparkle has built the system around a 6U chassis with strong power and
cooling capacity.

The top configuration uses five 2,700W titanium power supplies, reaching a combined 10,800W output, while the smaller version includes four 2,400W units rated at 7,200W.

With as many as 15 fans installed, the system has clearly been built to
manage heat effectively during continuous workloads.

Each GPU connects to the CPU through a PCIe 5.0 x8 interface, either directly or via a Microchip switch, maximizing data bandwidth while avoiding potential bottlenecks caused by shared links.

Theres support for dual M.2 slots and several NVMe and SATA bays for local storage.

Although theres no way of knowing at this stage how the Arc Pro B60 will perform in large-scale inference or training tasks, the flexibility offered
by the hardware could appeal to researchers and developers seeking affordable parallel compute power.

Unsurprisingly, Sparkle hasnt revealed pricing for the C741-6U-Dual 16P but potential buyers can make a purchase inquiry on the website .

Via Videocardz (Image credit: Sparkle)

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Link to news story: https://www.techradar.com/pro/cant-afford-nvidias-expensive-ai-accelerators-th en-consider-this-10-8kw-server-cluster-with-32-intel-gpus-and-768gb-vram


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