NVIDIA Launches Next-Gen Flagship GPU RTX 5090: The Strongest Performance Ever, Priced at 1999

On January 7, 2025, the highly anticipated CES Consumer Electronics Show officially opened in Las Vegas, USA. NVIDIA unveiled its next-generation flagship GPU in the RTX 50 series, with the RTX 5090 becoming the most expensive consumer-grade graphics card ever, priced at $1999. At the same time, it set a new benchmark for performance. Other models include the second-tier RTX 5080 priced at $999, the RTX 5070 Ti at $749, and the RTX 5070 at $549.
Hardware Specifications and Performance Breakthrough

The RTX 5090 is equipped with the brand-new GB202 GPU, featuring 21,760 CUDA cores, making it the first GeForce GPU to surpass 20,000 cores. This generation of graphics cards has all been upgraded to PCIe 5.0 interfaces, featuring DisplayPort 2.1a and a 16-pin power connector, and comes with the latest GDDR7 memory.

The flagship RTX 5090 offers 32GB of GDDR7 memory with a 512-bit memory interface and a memory speed of 26Gbps, with a power consumption of up to 575W. It provides three DP 2.1a ports and one HDMI 2.1 port, enhancing bandwidth and display output capabilities.

The second-tier RTX 5080 comes with 10,752 CUDA cores, 16GB of GDDR7 memory with a faster speed of 30Gbps, and a power consumption of 360W. According to official data, both the RTX 5080 and RTX 5090 are designed for high-end gamers and professional users, supporting extreme AI computing, video rendering, and gaming performance.
AI Performance Optimization and Professional Applications

Compared to the standard RTX 5090, the lighter version RTX 5090D offers slightly reduced AI computing performance but still maintains a strong output of up to 2375 TOPS, providing more options for developers and data scientists.

NVIDIA claims that the RTX 5090 achieves a new level of balance between performance and power consumption, offering powerful hardware support for next-generation AI, game development, and creative fields.
The Significance of High-Performance GPUs in AI Computing

High-performance GPUs have the following important significance for AI computing:

1. Enhancing Training Efficiency
   High-performance GPUs can significantly accelerate the training process of deep learning models. For instance, thousands of CUDA cores and hundreds of TOPS in AI computing power can enable large-scale parallel computations, reducing model training time and thus improving research and commercial development efficiency.

2. Supporting More Complex Models
   With the continuous advancement of AI technology, the scale and complexity of models are rapidly increasing. The large memory and high bandwidth of high-performance GPUs support larger parameter models, such as GPT and Vision Transformers, which can handle massive data and parameter computation requirements.

3. Real-Time Inference and Edge Computing
   In fields like autonomous driving, smart homes, and robotics, the real-time computational power of GPUs is crucial for complex scene inference. NVIDIA’s RTX series GPUs’ AI acceleration features enable efficient inference even on edge devices.

4. Democratizing AI Technology
   More powerful GPUs lower the entry barriers for AI technology, allowing more small and medium-sized enterprises, as well as independent developers, to access high-end computing resources, thus promoting the spread and innovation of AI technology.

The release of the NVIDIA RTX 50 series marks the beginning of a new era in GPU performance. Its AI computing capabilities will continue to drive innovation in artificial intelligence, scientific research, and the creative industry.