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AMD Radeon RX Vega 64

vs

NVIDIA GeForce GTX 1080

GPU Comparison Result

Below are the results of a comparison of AMD Radeon RX Vega 64 and NVIDIA GeForce GTX 1080 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

AMD Radeon RX Vega 64

Higher Bandwidth: 483.8 GB/s (483.8 GB/s vs 320.3 GB/s)
More Shading Units: 4096 (4096 vs 2560)
Newer Launch Date: August 2017 (August 2017 vs May 2016)

NVIDIA GeForce GTX 1080

Higher Boost Clock: 1733MHz (1546MHz vs 1733MHz)

Basic

AMD

Label Name

NVIDIA

August 2017

Launch Date

May 2016

Desktop

Platform

Desktop

Radeon RX Vega 64

Model Name

GeForce GTX 1080

Vega

Generation

GeForce 10

1247MHz

Base Clock

1607MHz

1546MHz

Boost Clock

1733MHz

PCIe 3.0 x16

Bus Interface

PCIe 3.0 x16

12,500 million

Transistors

7,200 million

Compute Units

256

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.

160

GlobalFoundries

Foundry

TSMC

14 nm

Process Size

16 nm

GCN 5.0

Architecture

Pascal

Memory Specifications

8GB

Memory Size

8GB

HBM2

Memory Type

GDDR5X

2048bit

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

945MHz

Memory Clock

1251MHz

483.8 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.

320.3 GB/s

Display and Media

1x HDMI 2.0b
3x DisplayPort 1.4a

Outputs

1x DVI
1x HDMI 2.0
3x DisplayPort 1.4a

Theoretical Performance

98.94 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.

110.9 GPixel/s

395.8 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.

277.3 GTexel/s

25.33 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.

138.6 GFLOPS

791.6 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.

277.3 GFLOPS

12.407 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.

8.696 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.

4096

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.

2560

16 KB (per CU)

L1 Cache

48 KB (per SM)

4MB

L2 Cache

2MB

295W

TDP

180W

1.2

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

2.1

OpenCL Version

3.0

4.6

OpenGL

4.6

CUDA

6.1

12 (12_1)

DirectX

12 (12_1)

2x 8-pin

Power Connectors

1x 8-pin

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.

6.4

Shader Model

6.4

600W

Suggested PSU

450W