Cenvalsa, distribuidor de componentes electrónicos, mecánicos e industriales
Este PDF será enviado a su cuenta de correo electrónico.
Por favor, asegúrese que el email es correcto:
MXM GPU MODULE NVIDIA RTX4070-8GB/65W
NVIDIA RTX4070/8GB GDDR6 MXM GPU Module for Edge AI computing , 82mm x 70mm with 65W low-power consumption to provide single-precision 15.71 TFLOPS and integer 321 TOPS computing capability.
- AI Chip : RTX4070 Ada Lovelace
- Memory : 8GB GDDR6 128bit
- Computing: 15.71 TFLOPS/321 TOPS/4608 CUDA/144 Tensor/36 RT Core
- Dimension : MXM 3.1 TYPE A : 82 x 70 mm
- 65W power consumption, no external PSU required: draw power directly from the MXM slot
- The best choice for embedded edge AI application
EGRX4708P65 is an MXM GPU Module specially designed for real edge applications. It is only 82 x 70mm. Under such an amazing size, it can output a single-precision computing power of up to 15.71 TFLOPS, the computing power converted into integer operations is also as high as 321 TOPS, and it has 4608 CUDA and 144 Tensor Core. In such a high computing power output, only 65W of power consumption can achieve excellent performance, seamless AI multitasking and amazing visual experience, all of which take place in an amazing small size.
EGRX4708P65 can be easily installed and integrated into a small AI computing pc and effectively solve the edge AI deployment with limited power supply. It can perform API transmission learning functions through the pre-training model, and then directly realize the fine-tuning model and low-latency reasoning at the edge.
What’s more shocking is that the EGRX4708P65 actually adopts the RTX4070 AI chip of NVIDIA’s latest ADA Lovelace architecture, which undoubtedly makes software developers more excited. The rich NVIDIA software eco system makes the edge AI deployment more fast and easy to implement, effectively solve the installation and low-latency reasoning of various AI models at the edge, and quickly make various decisions and judgments at the edge. Therefore, EGRX4708P65 is definitely the best choice for demanding AI tasks and limited space and limited power supply deployment among various edge equipment, whether it is industrial equipment, commercial game consoles or edge AI devices.
Specifications
Performance
