AMD Radeon Vega 8 vs AMD Radeon 660M
GPU Comparison Result
Below are the results of a comparison of AMD Radeon Vega 8 and AMD Radeon 660M video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Higher Boost Clock: 2000MHz (2000MHz vs 1900MHz)
- More Shading Units: 512 (512 vs 384)
- Newer Launch Date: January 2022 (January 2021 vs January 2022)
Basic
AMD
Label Name
AMD
January 2021
Launch Date
January 2022
Integrated
Platform
Integrated
Radeon Vega 8
Model Name
Radeon 660M
Cezanne
Generation
Rembrandt
300MHz
Base Clock
1500MHz
2000MHz
Boost Clock
1900MHz
IGP
Bus Interface
PCIe 4.0 x8
Memory Specifications
System Shared
Memory Size
System Shared
System Shared
Memory Type
System Shared
System Shared
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
SystemShared
Memory Clock
SystemShared
System Dependent
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
Theoretical Performance
16.00 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.
30.40 GPixel/s
64.00 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.
45.60 GTexel/s
4.096 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.
2.918 TFLOPS
128.0 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.
91.20 GFLOPS
2.089
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.
1.43
TFLOPS
Miscellaneous
512
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.
384
-
L1 Cache
128 KB per Array
-
L2 Cache
2MB
45W
TDP
15W
1.2
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.
1.2
2.1
OpenCL Version
2.0
Benchmarks
FP32 (float)
/ TFLOPS
Radeon Vega 8
2.089
+46%
Radeon 660M
1.43
Blender
Radeon Vega 8
62
Radeon 660M
92
+48%
