Home / GPU Comparison / AMD Instinct MI300X or AMD Radeon Instinct MI355X: What's better?

AMD Instinct MI300X

vs

AMD Radeon Instinct MI355X

GPU Comparison Result

Below are the results of a comparison of AMD Instinct MI300X and AMD Radeon Instinct MI355X video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

AMD Instinct MI300X

Higher Bandwidth: 5300 GB/s (5300 GB/s vs 8.19TB/s)

AMD Radeon Instinct MI355X

Larger Memory Size: 288GB (192GB vs 288GB)
Newer Launch Date: January 2025 (December 2023 vs January 2025)

Basic

AMD

Label Name

AMD

December 2023

Launch Date

January 2025

Desktop

Platform

Desktop

Instinct MI300X

Model Name

Radeon Instinct MI355X

Instinct

Generation

Radeon Instinct

1000MHz

Base Clock

1000 MHz

2100MHz

Boost Clock

2100 MHz

PCIe 5.0 x16

Bus Interface

PCIe 5.0 x16

Transistors

153 billion

Compute Units

304

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.

1216

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.

1216

Foundry

TSMC

Process Size

3 nm

Architecture

CDNA 4.0

Memory Specifications

192GB

Memory Size

288GB

HBM3

Memory Type

HBM3e

8192bit

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

5200MHz

Memory Clock

2000 MHz

5300 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.

8.19TB/s

Display and Media

Outputs

No outputs

Theoretical Performance

1496 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.

2553.6 GTexel/s

1300 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.

653.7 TFLOPS

81.7 TFLOPS

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.

81.72 TFLOPS

166.668 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.

83.354 TFLOPS

Miscellaneous

19456

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.

19456

16 KB (per CU)

L1 Cache

16 KB (per CU)

16MB

L2 Cache

16 MB

750W

TDP

1400W

OpenCL Version

3.0