Home / GPU Comparison / NVIDIA Quadro K4000 or Intel UHD Graphics 730: What's better?

NVIDIA Quadro K4000

vs

Intel UHD Graphics 730

GPU Comparison Result

Below are the results of a comparison of NVIDIA Quadro K4000 and Intel UHD Graphics 730 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA Quadro K4000

Larger Memory Size: 3GB (3GB vs System Shared)
Higher Bandwidth: 134.8 GB/s (134.8 GB/s vs System Dependent)
More Shading Units: 768 (768 vs 192)

Intel UHD Graphics 730

Newer Launch Date: March 2021 (March 2013 vs March 2021)

Basic

NVIDIA

Label Name

Intel

March 2013

Launch Date

March 2021

Professional

Platform

Integrated

Quadro K4000

Model Name

Intel UHD Graphics 730

Quadro

Generation

Intel UHD Graphics

PCIe 2.0 x16

Bus Interface

Ring Bus

2,540 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

28 nm

Process Size

Kepler

Architecture

Xe-LP (Gen12)

Memory Specifications

3GB

Memory Size

System Shared

GDDR5

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

1404MHz

Memory Clock

System Shared

134.8 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.

System Dependent

Display and Media

AV1 Encode/Decode

Decode Only

H.264 Hardware Encode/Decode

Yes

H.265 HEVC Hardware Encode/Decode

Yes

H.266 VVC Hardware Encode/Decode

Intel Quick Sync Video

Yes

1x DVI
2x DisplayPort 1.2

Outputs

Motherboard Dependent

Theoretical Performance

12.96 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.

51.84 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.

51.84 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.

1.219 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.

0.4992 TFLOPS

AI Features

Intel Deep Learning Boost on GPU

Miscellaneous

768

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.

192

16 KB (per SMX)

L1 Cache

384KB

L2 Cache

80W

TDP

1.1

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

3.0

CUDA

12 (11_0)

DirectX

12 (12_1)

1x 6-pin

Power Connectors

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.

5.1

Shader Model

6.6

250W

Suggested PSU