A unique single-slot, low-profile SRhonyra GeForce RTX 3060 graphics card that operates without an external power connector has appeared on Newegg with a price tag of $495.
Specifications and Design
The SRhonyra RTX 3060 Low Profile is built around the GA106 silicon and is equipped with 12 GB of VRAM. Cooling is handled by a compact blower-style fan. Physical dimensions measure 6.85 inches in length, 2.71 inches in width, and 0.70 inches in thickness. For display outputs, the unit provides a single HDMI 2.1 port and one DisplayPort 1.4a port.
Power Delivery
The most notable departure from standard RTX 3060 specifications is the complete absence of 6-pin or 8-pin auxiliary power connectors. The card relies strictly on the 70 W power delivery provided by the PCIe x16 slot. To achieve this, the printed circuit board incorporates shunt-modding to force operation well below the standard minimum power threshold established for NVIDIA's GA106 architecture.
Target Market and Value
Rather than targeting traditional gaming workloads, the Newegg listing markets the hardware specifically for artificial intelligence applications, positioning it as a compact solution for running local large language models ranging from 7 billion to 13 billion parameters.
At $495, buyers gain access to an ultra-compact, single-slot configuration tailored for restrictive small form factor systems that lack dedicated power cables. However, the strict 70 W power ceiling introduces significant performance compromises compared to standard desktop variants of the same GPU.
This specialized hardware design opens up intriguing possibilities for DIY enthusiasts attempting to upgrade enterprise pre-built systems, such as older office workstations from Dell or HP. These legacy motherboards frequently lack robust power supplies or auxiliary PCIe cables, making traditional GPU upgrades nearly impossible without a complete system overhaul. By circumventing the need for external power, the SRhonyra card allows such machines to be repurposed into capable AI nodes at a fraction of the cost of dedicated server hardware.
At the same time, prospective buyers must carefully weigh the financial investment against the inherent hardware limitations. While the 12 GB frame buffer is undeniably generous for handling quantized AI models locally, the heavily restricted power envelope will throttle processing speeds. Those planning to utilize the card for extended language model inference sessions should also monitor thermal performance closely, as the miniature blower-style cooler will need to work aggressively within such a confined single-slot footprint.
