Gigabyte GeForce RTX3090 EAGLE OC 24GB Graphics Card | Unboxing with अnबoxing देखो

GIGABYTE GeForce RTX 30 Series based on the NVIDIA Ampere architecture. With 2nd Gen RT Cores and 3rd Gen Tensor Cores, new streaming multiprocessors, and superfast GDDR6X, The RTX 3090 Eagle OC Decimates., Unit Price is ₹1,61,000/-

link to purchase from Amazon: https://www.amazon.in/Gigabyte-Graphi...

FEATURES

NVIDIA Ampere Streaming Multiprocessors
2nd Generation RT Cores
3rd Generation Tensor Cores
Powered by GeForce RTX™ 3090
Integrated with 24GB GDDR6X 384-bit memory interface
WINDFORCE 3X Cooling System with alternate spinning fans
RGB Fusion 2.0
Protection metal back plate

Core Clock

TBD MHz

MODEL GV-N3090EAGLE-OC-24GD
CHIPSET NVIDIA GEFORCE
GPU RTX 3090
PCI EXPRESS 4.0
MEMORY CLOCK 19.5 Gbps
MEMORY SIZE 24 GB
MEMORY INTERFACE 384-BIT
MEMORY TYPE GDDR6X
DIRECT X SUPPORT 12
OPEN GL 4.6
PORTS
HDMI Output : Yes x 2 (Native) (HDMI 2.1)
Display Port : Yes x 3 (Native) (DisplayPort 1.4)
RESOLUTION 7680x4320
COOLER WINDFORCE 3X
DUAL-LINK DVI SUPPORTED NA
SOFTWARE Drivers and Software
PACKAGE CONTENTS Graphics Card, User Manual
GPU CORE (CUDA CORE) 10496
SLI SUPPORTED Yes
POWER CONNECTORS 2 x 8 Pin
WARRANTY 3 Years

The Nvidia RTX 3090 is a powerful tool not just for gaming, but also for a wide range of professional and creative applications, is also highly versatile and can be used for a variety of other applications, including:


Content Creation:

Video Editing: The RTX 3090's powerful GPU acceleration can significantly speed up rendering and editing processes in software like Adobe Premiere Pro.
3D Rendering: Applications like Blender, Autodesk Maya, and Cinema 4D benefit from the RTX 3090's capabilities, especially with ray tracing and real-time rendering.

Machine Learning and AI:

The RTX 3090 is suitable for training and inference in machine learning models due to its CUDA cores and Tensor cores, which enhance performance in deep learning frameworks like TensorFlow and PyTorch.

Scientific Computing:

Researchers can leverage the RTX 3090 for simulations, data analysis, and computational tasks in fields like physics, chemistry, and biology, where GPU acceleration can lead to significant performance improvements.

Cryptocurrency Mining:

The RTX 3090 can be used for mining cryptocurrencies, particularly those that benefit from high hash rates. However, profitability can vary widely based on market conditions and power costs.

Virtual Reality (VR) and Augmented Reality (AR):

The card can power immersive VR and AR experiences, making it valuable for developers and users in these fields.

Software Development:

Developers can use the RTX 3090 for building and testing applications that require high graphical performance or parallel processing capabilities.

Data Visualization:

The RTX 3090 can handle complex visualizations and large datasets effectively, making it useful for professionals in data analysis and business intelligence.

Streaming:

With its capabilities, the RTX 3090 can enhance live streaming quality, providing better performance for streamers who use software like OBS Studio or XSplit.


The RTX3090 is quite a powerful supercomputer and a good component for a Machine Learning Workstation. It’s internal 24GB GDDR6X memory with a 384 bit memory bus makes it perfect for larger ML models, and it’s 10,496 CUDA cores give it a lot of power!!! (CUDA is an open souce library by NVIDIA that allows the use of GPU cores for very fast math operations and is in my opinion the foundation to the great success of NVIDIA in the Machine Learning Space).

For Machine Learning models that are aware of tensor cores, this card comes with a whopping 328 3rd generation cores, resulting in even shorter processing times.

A sample application of Machine Learning is the processing of video frames for object detection and tracking including face recognition, where this card is capable of processing in excess of 2000 frames per second from multiple camera feeds (this depends on the ML model being used).

Other applications that benefit from these capabilities are in video editing, engineering design, such in the element design of buildings or machines, and any application based on matrix processing.

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