Home / GPU Comparison / NVIDIA GRID K2 or Intel Arc A380: What's better?

NVIDIA GRID K2

vs

Intel Arc A380

GPU Comparison Result

Below are the results of a comparison of NVIDIA GRID K2 and Intel Arc A380 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA GRID K2

More Shading Units: 1536 (1536 vs 1024)

Intel Arc A380

Larger Memory Size: 6GB (4GB vs 6GB)
Higher Bandwidth: 186.0 GB/s (160.0 GB/s vs 186.0 GB/s)
Newer Launch Date: June 2022 (May 2013 vs June 2022)

Basic

NVIDIA

Label Name

Intel

May 2013

Launch Date

June 2022

Professional

Platform

Desktop

GRID K2

Model Name

Arc A380

GRID

Generation

Alchemist

Base Clock

2000MHz

Boost Clock

2050MHz

PCIe 3.0 x16

Bus Interface

PCIe 4.0 x8

3,540 million

Transistors

7,200 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.

128

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

28 nm

Process Size

6 nm

Kepler

Architecture

Generation 12.7

Memory Specifications

4GB

Memory Size

6GB

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.

96bit

1250MHz

Memory Clock

1937MHz

160.0 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.

186.0 GB/s

Display and Media

No outputs

Outputs

1x HDMI 2.1
3x DisplayPort 2.0

Theoretical Performance

23.84 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.

65.60 GPixel/s

95.36 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.

131.2 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.

8.397 TFLOPS

95.36 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.

2.243 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.

4.282 TFLOPS

Miscellaneous

1536

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.

1024

16 KB (per SMX)

L1 Cache

512KB

L2 Cache

4MB

225W

TDP

75W

1.2.175

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

3.0

4.6

OpenGL

4.6

3.0

CUDA

12 (11_0)

DirectX

12 Ultimate (12_2)

1x 6-pin + 1x 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.

6.5 (5.1)

Shader Model

6.6

550W

Suggested PSU

250W