AMD will lead the graphics card market with RDNA 3

The RTX 4000 series and Radeon RX 7000 family, which are expected to be introduced this year, will take the competition in the graphics card market to the next level. To be used in AMD Radeon RX 7000 series RDNA 3 architecturemay surpass Nvidia.

Both AMD and Nvidia will use chips produced by TSMC with 5nm technology in the graphics cards they will introduce this year. According to the leaked information, the GPU area of ​​AD102 will be less than its rival Navi 31. It is estimated that the RDNA 3 architecture will consume less power than its competitor. According to the leaked information, power consumption will be 500W in Navi 31 and 600W in AD102.


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AMD RDNA 3 will surpass Nvidia Ada Lovelace architecture

Nvidia AD102, 18,432 CUDAs will be presented to users with its core. If the FP32 core value of AMD Navi 31 is 15.360 Stream Processor it will be. Navi 31, 3.0GHz The GPU will surpass the AD102 in clock speed.

AMD RDNA 3 will surpass Nvidia Ada Lovelace architecture

It is stated that AMD will be one step ahead of its competitors in GPU memory. While the GPU memory of the Navi 31 is 32 GB, the AD102 will have only 24 GB of memory.

AD102 100 TFLOP, built on Ada Lovelace architecture, and Navi 31, which will be introduced with RDNA 3 architecture, will have 92 TFLOPs of FP32 performance. It is estimated that both companies will launch their new graphics cards in the third or fourth quarter of 2022.

AD102 NAVI 31
Fabrication Process TSMC N5 TSMC N5/N6
GPU Architecture Nvidia Island lovelace AMD RDNA3
Estimated GPU space 600mm² 800mm²
GPU Cluster 12 Graphics Processing Clusters (GPC) 2×3 Shader Engine
GPU Texture Set 72 Texture Processing Clusters (TPC) 2×30 RDNA Workgroups (WGP)
FP32 Kernel 18,432 CUDAs 15.360 Stream Processors
GPU Clock Speed 2.7GHz 3.0GHz
GPU Memory 24GB GDDR6X 32GB GDDR6
Memory Bandwidth 21Gbps 384-bit 18 Gbps 256-bit
cache 96MB (L2) 512MB Infinity Cache
Power consumption 600W 500W
Introduction Date 2022 2022
FP32 Performance 100 TFLOPS 92 TFLOPS

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