AMD Radeon RX 7900 GRE vs NVIDIA RTX 5880 Ada Generation
GPU Comparison Result
Below are the results of a comparison of AMD Radeon RX 7900 GRE and NVIDIA RTX 5880 Ada Generation video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Higher Boost Clock: 2550MHz (2245MHz vs 2550MHz)
- Larger Memory Size: 48GB (16GB vs 48GB)
- Higher Bandwidth: 864.0 GB/s (576.0 GB/s vs 864.0 GB/s)
- More Shading Units: 14080 (5120 vs 14080)
- Newer Launch Date: January 2024 (July 2023 vs January 2024)
Basic
AMD
Label Name
NVIDIA
July 2023
Launch Date
January 2024
Desktop
Platform
Desktop
Radeon RX 7900 GRE
Model Name
RTX 5880 Ada Generation
Navi III
Generation
Quadro Ada
1287MHz
Base Clock
1155MHz
2245MHz
Boost Clock
2550MHz
PCIe 4.0 x16
Bus Interface
PCIe 4.0 x16
57,700 million
Transistors
-
80
RT Cores
-
80
Compute Units
-
320
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
-
TSMC
Foundry
-
5 nm
Process Size
-
RDNA 3.0
Architecture
-
Memory Specifications
16GB
Memory Size
48GB
GDDR6
Memory Type
GDDR6
256bit
Memory Bus
?
The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.
384bit
2250MHz
Memory Clock
2250MHz
576.0 GB/s
Bandwidth
?
Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.
864.0 GB/s
Theoretical Performance
431.0 GPixel/s
Pixel Rate
?
Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.
448.8 GPixel/s
718.4 GTexel/s
Texture Rate
?
Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.
1122 GTexel/s
91.96 TFLOPS
FP16 (half)
?
An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.
71.81 TFLOPS
1437 GFLOPS
FP64 (double)
?
An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
1122 GFLOPS
46.9
TFLOPS
FP32 (float)
?
An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
70.374
TFLOPS
Miscellaneous
-
SM Count
?
Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.
110
5120
Shading Units
?
The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.
14080
256 KB per Array
L1 Cache
128 KB (per SM)
6MB
L2 Cache
72MB
260W
TDP
285W
1.3
Vulkan Version
?
Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.
-
2.2
OpenCL Version
-
4.6
OpenGL
-
12 Ultimate (12_2)
DirectX
-
2x 8-pin
Power Connectors
-
6.7
Shader Model
-
192
ROPs
?
The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.
-
600W
Suggested PSU
-
Benchmarks
FP32 (float)
/ TFLOPS
Radeon RX 7900 GRE
46.9
RTX 5880 Ada Generation
70.374
+50%
