Home / GPU Comparison / NVIDIA RTX PRO 1000 Blackwell Mobile or Intel Graphics 32EU (Arrow Lake): What's better?

NVIDIA RTX PRO 1000 Blackwell Mobile

vs

Intel Graphics 32EU (Arrow Lake)

GPU Comparison Result

Below are the results of a comparison of NVIDIA RTX PRO 1000 Blackwell Mobile and Intel Graphics 32EU (Arrow Lake) video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA RTX PRO 1000 Blackwell Mobile

Higher Boost Clock: 2520 MHz (2520 MHz vs 1800 MHz)
Larger Memory Size: 8GB (8GB vs System Shared)
Higher Bandwidth: 448.0GB/s (448.0GB/s vs System Dependent)
More Shading Units: 2560 (2560 vs 256)
Newer Launch Date: March 2025 (March 2025 vs January 2025)

Basic

NVIDIA

Label Name

Intel

March 2025

Launch Date

January 2025

Mobile

Platform

Integrated

Former Codename

Arrow Lake-S

GPU Lithography

TSMC N5P

RTX PRO 1000 Blackwell Mobile

Model Name

Intel Graphics

Blackwell-MW

Generation

Xe-LPG (Arrow Lake-S)

2235 MHz

Base Clock

300 MHz

2520 MHz

Boost Clock

1800 MHz

PCIe 5.0 x16

Bus Interface

Unknown

Transistors

RT Cores

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.

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.

TSMC

Foundry

TSMC

5 nm

Process Size

5 nm

Blackwell 2.0

Architecture

Xe-LPG

Memory Specifications

8GB

Memory Size

System Shared

GDDR7

Memory Type

DDR5 (System Shared)

128bit

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

1750 MHz

Memory Clock

System Dependent

448.0GB/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.

System Dependent

Display and Media

AV1 Encode/Decode

Yes

DisplayPort Extensions

DisplayPort 2.1 UHBR20

H.264 Hardware Encode/Decode

Yes

H.265 HEVC Hardware Encode/Decode

Yes

HDMI Version

HDMI 2.1 FRL

Intel Quick Sync Video

Yes

Max Resolution DP

7680 x 4320 @ 60Hz

Max Resolution eDP

3840 x 2400 @ 120Hz

Max Resolution HDMI

4096 x 2304 @ 60Hz (HDMI 2.1 TMDS); 7680 x 4320 @ 60Hz (HDMI 2.1 FRL)

Max Video Decode Bandwidth

Up to 8K 60 FPS 10-bit HDR

Max Video Encode Bandwidth

Up to 8K 120 FPS 10-bit HDR

Number of Displays Supported

Portable Device Dependent

Outputs

eDP 1.4b, DisplayPort 2.1 UHBR20, HDMI 2.1 FRL

Theoretical Performance

80.64 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.

14.4 GPixel/s

201.6 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.

28.8 GTexel/s

12.90 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.

201.6 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.

12.642 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.

0.9216 TFLOPS

AI Features

AI Software Frameworks Supported by GPU

OpenVINO, WindowsML, DirectML, ONNX RT, WebGPU

GPU Peak TOPS (Int8)

4 TOPS

Intel Deep Learning Boost on GPU

Yes

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.

2560

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.

256

128 KB (per SM)

L1 Cache

32 MB

L2 Cache

35W

TDP

1.4

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

4.5

10.1

CUDA

12 Ultimate (12_2)

DirectX

DirectX 12 Ultimate (12_2)

None

Power Connectors

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.

6.8

Shader Model

6.8