NVIDIA and Advanced Micro Devices (AMD) are two of the largest and most well-known manufacturers of graphics processing units (GPUs), which are specialized processors designed to improve performance in tasks that require intensive computations, such as video gaming, video rendering, and machine learning.
NVIDIA, founded in 1993, designs and manufactures GPUs for a wide range of markets, including gaming, professional visualization, and data centers. The company’s product line includes the GeForce line of consumer GPUs, the Quadro line of professional GPUs, and the Tesla line of data center GPUs. NVIDIA is known for its focus on gaming and AI/ML related applications. The company has a broad portfolio of products, with something for every use case and budget, and it has a strong track record of providing software support, game-ready driver updates and optimised performance on games.
AMD, founded in 1969, also designs and manufactures GPUs for a wide range of markets, including gaming, professional visualization, and data centers. The company’s product line includes the Radeon line of consumer and professional GPUs, and the Instinct line of data center GPUs. AMD has a good track record in providing professional and datacenter-grade products, with a good performance/price point.
Both companies have achieved significant success in the GPU market, but NVIDIA has historically been the dominant player, with a larger market share and a stronger focus on gaming and AI/ML. AMD has been competitive with its offerings and has recently released a new generation of GPUs that have competitive performance for gaming and professional use cases.
In summary, both NVIDIA and AMD are large and well-known manufacturers of GPUs, each with their own strengths and focus areas. NVIDIA has a broader range of products, a more mature software ecosystem, and a stronger focus on gaming, AI/ML and professional visualization applications, while AMD has a more competitive pricing and good performance/price point on its products. The choice between the two will depend on the specific use case, the requirements of the application, and budget