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NVIDIA RTX 5880 Ada Generation

NVIDIA RTX 5880 Ada Generation

NVIDIA RTX 5880 Ada Generation is a Desktop video accelerator from NVIDIA. It began to be released in January 2024. The GPU has a boost frequency of 2550MHz. It also has a memory frequency of 2250MHz. Its characteristics, as well as benchmark results, are presented in more detail below.

New this year
Top Desktop GPU: 16

Basic

Label Name
NVIDIA
Platform
Desktop
Launch Date
January 2024
Model Name
RTX 5880 Ada Generation
Generation
Quadro Ada
Base Clock
1155MHz
Boost Clock
2550MHz
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
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
L1 Cache
128 KB (per SM)
L2 Cache
72MB
Bus Interface
PCIe 4.0 x16
TDP
285W

Memory Specifications

Memory Size
48GB
Memory Type
GDDR6
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
Memory Clock
2250MHz
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

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
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
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
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
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.
71.789 TFlops

FP32 (float)

71.789 TFlops

Compared to Other GPU

76%
87%
97%
Better then 76% GPU over the past year
Better then 87% GPU over the past 3 years
Better then 97% GPU

SiliconCat Rating

16
Ranks 16 among Desktop GPU on our website
21
Ranks 21 among all GPU on our website
FP32 (float)
Instinct MI300X
AMD, December 2023
163.351 TFlops
L40G
NVIDIA, October 2022
89.942 TFlops
RTX 5880 Ada Generation
NVIDIA, January 2024
71.789 TFlops
Radeon PRO W7900
AMD, April 2023
61.302 TFlops
H100 PCIe
NVIDIA, March 2022
51.205 TFlops

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