Last Updated： Aggregation Period:Dec 31, 2025～Jan 27, 2026
This ranking is based on the number of page views on our site.
Last Updated： Aggregation Period:Dec 31, 2025～Jan 27, 2026
This ranking is based on the number of page views on our site.
Last Updated： Aggregation Period:Dec 31, 2025～Jan 27, 2026
This ranking is based on the number of page views on our site.
1～7 item / All 7 items
"Pocket AI," a portable GPU accelerator equipped with NVIDIA RTX A500.
Pocket AI offers ultimate flexibility and reliability on the go. This portable plug-and-play AI accelerator provides the perfect power/performance balance from NVIDIA RTX GPUs. Pocket AI is the ideal device for AI developers, professional graphics users, and embedded industrial applications, enhancing productivity by improving work efficiency.
Unlock the potential of AI on the go with NVIDIA RTX GPU! Build a high-performance work environment.
"Pocket AI" is a compact product that combines high flexibility and reliability, allowing it to be used as an AI accelerator on the go. It supports plug-and-play and offers an excellent power-performance balance utilizing the NVIDIA RTX A500. It is suitable for the work environments of AI developers and professional graphic users, as well as for field applications in the embedded industrial sector, contributing to increased productivity through accelerated processing. The Thunderbolt interface used in this product is a high-speed communication standard that has become popular in laptops, thin clients, and compact PCs. With the evolution to version 4.0 (backward compatible with 3.0) and the adoption of USB Type-C connections, peripheral devices and gadgets utilizing this technology are continuously emerging. By leveraging the optical transfer speed of Thunderbolt (up to 40Gb/s) and the general availability of hosts, it achieves an intuitive plug-and-play UX that significantly enhances productivity.
40 TOPS M.2 AI Accelerator Module
The Geniatech AI accelerator module, adopting the M.2 form factor, can be seamlessly integrated into PCs and edge devices, enabling real-time deep neural network inference with low power consumption across various applications.
NVIDIA RTX PRO 6000 BW, 96GB GDDR7, PCIe Gen5 x16, 2.1
【ADLINK RTX PRO 6000 Blackwell Server Edition Features】 ■ NVIDIA Blackwell Architecture ■ Equipped with 96GB GDDR7 Memory ■ PCIe Gen5 x16 Interface ■ 24,064 CUDA Cores, 188 RT Cores, 752 Tensor Cores ■ Supports up to 4 DisplayPort 2.1 Outputs, TGP 600W ■ Designed for Servers and Workstations
As an AI inference engine, it is suitable for small embedded systems! Compatible with Intel's OpenVINO toolkit.
The "Mustang-M2BM-MX2" is an AI accelerator equipped with two Intel Movidius Myriad X VPU MA2485s. Due to its low power consumption and high performance, it is suitable for DNN topology, making it ideal for AI edge computing, and it allows for longer operation in battery-powered devices. Additionally, we also offer the "Mustang-MPCIE-MX2" with a miniPCIe interface and the "Mustang-V100-MX4." 【Features】 ■ M.2 BM interface (22 x 80mm) ■ 2 x Intel Movidius Myriad X VPU MA2485 ■ Power consumption: approximately 7.5W ■ Operating temperature: -20°C to 60°C ■ Compatible with Intel's OpenVINO toolkit *For more details, please refer to the PDF document or feel free to contact us.
40 TOPS M.2 AI Accelerator Module
The Geniatech AI accelerator module, adopting the M.2 form factor, can be seamlessly integrated into PCs and edge devices, enabling real-time deep neural network inference with low power consumption across various applications.
AI accelerator capable of supporting everything from CNN models to generative AI models.
EdgeCortix SAKURA-II is a cutting-edge AI accelerator that offers industry-leading efficiency through the company's low-latency Dynamic Neural Accelerator (DNA). It is a low-power silicon device that delivers excellent performance with a small footprint, designed for applications requiring fast, real-time AI inference with a batch size of one. SAKURA-II is designed to handle the most challenging generative AI applications at the edge, allowing designers to create new content based on heterogeneous inputs such as images, text, and sound. Within a power envelope of 8W (standard value), it supports billion-parameter models like Llama 2 or 3, Stable Diffusion, DETR, and ViT, meeting the requirements for a vast number of edge generative AI applications across vision, language, speech, and many other domains.
