AMD Radeon 680M vs AMD Radeon 660M

GPU Comparison Result

Below are the results of a comparison of AMD Radeon 680M and AMD Radeon 660M video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

  • Higher Boost Clock: 2200MHz (2200MHz vs 1900MHz)
  • More Shading Units: 768 (768 vs 384)

Basic

AMD
Label Name
AMD
January 2022
Launch Date
January 2022
Integrated
Platform
Integrated
Radeon 680M
Model Name
Radeon 660M
Navi II IGP
Generation
Rembrandt
2000MHz
Base Clock
1500MHz
2200MHz
Boost Clock
1900MHz
PCIe 4.0 x8
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

70.40 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
105.6 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
6.758 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
211.2 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
3.311 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

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.
384
128 KB per Array
L1 Cache
128 KB per Array
2MB
L2 Cache
2MB
50W
TDP
15W
1.3
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
2.0
OpenCL Version
2.0

Benchmarks

FP32 (float) / TFLOPS
Radeon 680M
3.311 +132%
Radeon 660M
1.43
3DMark Time Spy
Radeon 680M
2399 +57%
Radeon 660M
1526
Blender
Radeon 680M
249 +171%
Radeon 660M
92