Home / GPU Comparison / AMD Radeon PRO W7900 or AMD Radeon AI PRO R9700: What's better?

AMD Radeon PRO W7900

vs

AMD Radeon AI PRO R9700

GPU Comparison Result

Below are the results of a comparison of AMD Radeon PRO W7900 and AMD Radeon AI PRO R9700 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

AMD Radeon PRO W7900

Larger Memory Size: 48GB (48GB vs 32GB)
Higher Bandwidth: 864.0 GB/s (864.0 GB/s vs 644.6GB/s)
More Shading Units: 6144 (6144 vs 4096)

AMD Radeon AI PRO R9700

Higher Boost Clock: 2920 MHz (2495MHz vs 2920 MHz)
Newer Launch Date: July 2025 (April 2023 vs July 2025)

Basic

AMD

Label Name

AMD

April 2023

Launch Date

July 2025

Professional

Platform

Desktop

Radeon PRO W7900

Model Name

Radeon AI PRO R9700

Radeon Pro Navi

Generation

Radeon Pro Navi

1855MHz

Base Clock

1660 MHz

2495MHz

Boost Clock

2920 MHz

PCIe 4.0 x16

Bus Interface

PCIe 5.0 x16

57,700 million

Transistors

53.9 billion

RT Cores

Compute Units

Tensor Cores

Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.

128

384

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.

256

TSMC

Foundry

TSMC

5 nm

Process Size

4 nm

RDNA 3.0

Architecture

RDNA 4.0

Memory Specifications

48GB

Memory Size

32GB

GDDR6

Memory Type

GDDR6

384bit

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.

256bit

2250MHz

Memory Clock

2518 MHz

864.0 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.

644.6GB/s

Display and Media

3x DisplayPort 2.1
1x mini-DisplayPort 2.1

Outputs

4x DisplayPort 2.1a

Theoretical Performance

479.0 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.

373.8 GPixel/s

958.1 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.

747.5 GTexel/s

122.6 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.

95.68 TFLOPS

1.916 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.

1495 GFLOPS

62.546 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.

48.797 TFLOPS

Miscellaneous

6144

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.

4096

256 KB per Array

L1 Cache

6MB

L2 Cache

8 MB

295W

TDP

300W

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.

1.3

2.2

OpenCL Version

2.2

4.6

OpenGL

4.6

12 Ultimate (12_2)

DirectX

12 Ultimate (12_2)

2x 8-pin

Power Connectors

1x 16-pin

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.

128

6.7

Shader Model

6.8

600W

Suggested PSU

700 W