Intel Arc A350M vs NVIDIA GeForce MX550
GPU Comparison Result
Below are the results of a comparison of Intel Arc A350M and NVIDIA GeForce MX550 video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Larger Memory Size: 4GB (4GB vs 2GB)
- Higher Bandwidth: 112.0 GB/s (112.0 GB/s vs 96.00 GB/s)
- Newer Launch Date: March 2022 (March 2022 vs January 2022)
- Higher Boost Clock: 1320MHz (1150MHz vs 1320MHz)
- More Shading Units: 1024 (768 vs 1024)
Basic
Intel
Label Name
NVIDIA
March 2022
Launch Date
January 2022
Mobile
Platform
Mobile
Arc A350M
Model Name
GeForce MX550
Alchemist
Generation
GeForce MX
300MHz
Base Clock
1065MHz
1150MHz
Boost Clock
1320MHz
PCIe 4.0 x8
Bus Interface
PCIe 4.0 x8
7,200 million
Transistors
4,700 million
6
RT Cores
-
48
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.
32
TSMC
Foundry
TSMC
6 nm
Process Size
12 nm
Generation 12.7
Architecture
Turing
Memory Specifications
4GB
Memory Size
2GB
GDDR6
Memory Type
GDDR6
64bit
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.
64bit
1750MHz
Memory Clock
1500MHz
112.0 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.
96.00 GB/s
Theoretical Performance
27.60 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.
21.12 GPixel/s
55.20 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.
42.24 GTexel/s
3.533 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.
2.703 TFLOPS
441.6 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.
42.24 GFLOPS
1.801
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.
2.757
TFLOPS
Miscellaneous
-
SM Count
?
Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.
16
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.
1024
-
L1 Cache
128 KB (per SM)
4MB
L2 Cache
2MB
25W
TDP
25W
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.
1.3
3.0
OpenCL Version
3.0
4.6
OpenGL
4.6
12 Ultimate (12_2)
DirectX
12 (12_1)
-
CUDA
7.5
-
Power Connectors
None
24
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.
16
6.6
Shader Model
6.6
Benchmarks
FP32 (float)
/ TFLOPS
Arc A350M
1.801
GeForce MX550
2.757
+53%
3DMark Time Spy
Arc A350M
2758
+16%
GeForce MX550
2380
