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AMD Instinct MI300X Accelerator

vs

AMD Instinct MI300X

GPU Comparison Result

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

Advantages

AMD Instinct MI300X

Newer Launch Date: December 2023 (December 2023 vs December 2023)

Basic

AMD

Label Name

AMD

December 2023

Launch Date

December 2023

Desktop

Platform

Desktop

Instinct MI300X

Model Name

Instinct MI300X

Instinct

Generation

Instinct

1000MHz

Base Clock

1000MHz

2100MHz

Boost Clock

2100MHz

PCIe 5.0 x16

Bus Interface

PCIe 5.0 x16

Memory Specifications

192GB

Memory Size

192GB

HBM3

Memory Type

HBM3

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

5200MHz

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.

5300 GB/s

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.

1496 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.

1300 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.

81.7 TFLOPS

160.132 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.

166.668 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

16MB

750W

TDP

750W