Home / GPU Comparison / NVIDIA GeForce GTX 1070 or AMD Radeon Pro 5500 XT: What's better?

NVIDIA GeForce GTX 1070

vs

AMD Radeon Pro 5500 XT

GPU Comparison Result

Below are the results of a comparison of NVIDIA GeForce GTX 1070 and AMD Radeon Pro 5500 XT video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA GeForce GTX 1070

Higher Bandwidth: 256.3 GB/s (256.3 GB/s vs 224.0 GB/s)
More Shading Units: 1920 (1920 vs 1536)

AMD Radeon Pro 5500 XT

Higher Boost Clock: 1757MHz (1683MHz vs 1757MHz)
Newer Launch Date: August 2020 (June 2016 vs August 2020)

Basic

NVIDIA

Label Name

AMD

June 2016

Launch Date

August 2020

Desktop

Platform

Desktop

GeForce GTX 1070

Model Name

Radeon Pro 5500 XT

GeForce 10

Generation

Radeon Pro Mac

1506MHz

Base Clock

1187MHz

1683MHz

Boost Clock

1757MHz

PCIe 3.0 x16

Bus Interface

PCIe 4.0 x8

7,200 million

Transistors

6,400 million

Compute Units

120

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

TSMC

16 nm

Process Size

7 nm

Pascal

Architecture

RDNA 1.0

Memory Specifications

8GB

Memory Size

8GB

GDDR5

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.

128bit

2002MHz

Memory Clock

1750MHz

256.3 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.

224.0 GB/s

Display and Media

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

Outputs

No outputs

Theoretical Performance

107.7 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.

56.22 GPixel/s

202.0 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.

168.7 GTexel/s

101.0 GFLOPS

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.

10.80 TFLOPS

202.0 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.

337.3 GFLOPS

6.592 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.

5.506 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.

1920

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.

1536

48 KB (per SM)

L1 Cache

2MB

L2 Cache

2MB

150W

TDP

125W

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

3.0

OpenCL Version

2.1

4.6

OpenGL

4.6

6.1

CUDA

12 (12_1)

DirectX

12 (12_1)

1x 8-pin

Power Connectors

None

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

6.5

450W

Suggested PSU

300W