Home / GPU Comparison / NVIDIA GeForce GTX 1660 SUPER or Intel UHD Graphics 48EU: What's better?

NVIDIA GeForce GTX 1660 SUPER

vs

Intel UHD Graphics 48EU

GPU Comparison Result

Below are the results of a comparison of NVIDIA GeForce GTX 1660 SUPER and Intel UHD Graphics 48EU video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA GeForce GTX 1660 SUPER

Larger Memory Size: 6GB (6GB vs System Shared)
Higher Bandwidth: 336.0 GB/s (336.0 GB/s vs System Dependent)
More Shading Units: 1408 (1408 vs 384)

Intel UHD Graphics 48EU

Newer Launch Date: September 2020 (October 2019 vs September 2020)

Basic

NVIDIA

Label Name

Intel

October 2019

Launch Date

September 2020

Desktop

Platform

Integrated

Former Codename

Tiger Lake GT2

GPU Lithography

10 nm SuperFin

GeForce GTX 1660 SUPER

Model Name

Intel UHD Graphics Xe G4 48EUs

GeForce 16

Generation

Tiger Lake

1530MHz

Base Clock

1785MHz

Boost Clock

PCIe 3.0 x16

Bus Interface

Ring Bus

6,600 million

Transistors

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.

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

Intel

12 nm

Process Size

10 nm SuperFin

Turing

Architecture

Xe-LP (Generation 12.1)

Memory Specifications

6GB

Memory Size

System Shared

GDDR6

Memory Type

System Shared

192bit

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.

System Shared

1750MHz

Memory Clock

System Shared

336.0 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.

System Dependent

Display and Media

AV1 Encode/Decode

Decode Only

DisplayPort Extensions

1.4

H.264 Hardware Encode/Decode

Yes

H.265 HEVC Hardware Encode/Decode

Yes

HDMI Version

2.0b

Intel Quick Sync Video

Yes

Max Resolution DP

7680 x 4320 @ 60Hz

Max Resolution eDP

4096 x 2304 @ 60Hz

Max Resolution HDMI

4096 x 2304 @ 60Hz

Number of Displays Supported

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

Outputs

eDP 1.4b, MIPI-DSI 2.0, DP 1.4, HDMI 2.0b

Theoretical Performance

85.68 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.

157.1 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.

10.05 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.

157.1 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.

4.926 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.

0.8832 TFLOPS

AI Features

AI Software Frameworks Supported by GPU

Intel oneAPI, oneDNN, oneMKL

Intel Deep Learning Boost on GPU

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.

1408

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.

384

64 KB (per SM)

L1 Cache

1536KB

L2 Cache

125W

TDP

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.

1.4

3.0

OpenCL Version

3.0

4.6

OpenGL

4.6

7.5

CUDA

12 (12_1)

DirectX

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.

6.6

Shader Model

300W

Suggested PSU