Home / GPU Comparison / NVIDIA Quadro K4000 or Intel Data Center GPU Max 1100: What's better?

NVIDIA Quadro K4000

vs

Intel Data Center GPU Max 1100

GPU Comparison Result

Below are the results of a comparison of NVIDIA Quadro K4000 and Intel Data Center GPU Max 1100 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

Intel Data Center GPU Max 1100

Larger Memory Size: 48GB (3GB vs 48GB)
Higher Bandwidth: 1229 GB/s (134.8 GB/s vs 1229 GB/s)
More Shading Units: 7168 (768 vs 7168)
Newer Launch Date: January 2023 (March 2013 vs January 2023)

Basic

NVIDIA

Label Name

Intel

March 2013

Launch Date

January 2023

Professional

Platform

Professional

Quadro K4000

Model Name

Data Center GPU Max 1100

Quadro

Generation

Data Center GPU

Base Clock

1000MHz

Boost Clock

1550MHz

PCIe 2.0 x16

Bus Interface

PCIe 5.0 x16

2,540 million

Transistors

100,000 million

RT Cores

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.

448

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.

448

TSMC

Foundry

Intel

28 nm

Process Size

10 nm

Kepler

Architecture

Generation 12.5

Memory Specifications

3GB

Memory Size

48GB

GDDR5

Memory Type

HBM2e

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.

8192bit

1404MHz

Memory Clock

600MHz

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.

1229 GB/s

Display and Media

1x DVI
2x DisplayPort 1.2

Outputs

No outputs

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.

694.4 GTexel/s

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.

22.22 TFLOPS

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.

22.22 TFLOPS

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.

21.776 TFLOPS

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.

7168

16 KB (per SMX)

L1 Cache

64 KB (per EU)

384KB

L2 Cache

204MB

80W

TDP

300W

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.

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

1x 12-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.

5.1

Shader Model

6.6

250W

Suggested PSU

700W