Home / GPU Comparison / Intel UHD Graphics 770 or NVIDIA RTX 3500 Embedded Ada Generation: What's better?

Intel UHD Graphics 770

vs

NVIDIA RTX 3500 Embedded Ada Generation

GPU Comparison Result

Below are the results of a comparison of Intel UHD Graphics 770 and NVIDIA RTX 3500 Embedded Ada Generation video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

Intel UHD Graphics 770

Higher Boost Clock: 1450-1660 MHz (CPU dependent) (1450-1660 MHz (CPU dependent) vs 2250MHz)

NVIDIA RTX 3500 Embedded Ada Generation

Larger Memory Size: 12GB (System Shared vs 12GB)
Higher Bandwidth: 432.0 GB/s (System Dependent vs 432.0 GB/s)
More Shading Units: 5120 (256 vs 5120)
Newer Launch Date: March 2023 (November 2021 vs March 2023)

Basic

Intel

Label Name

NVIDIA

November 2021

Launch Date

March 2023

Integrated

Platform

Desktop

Alder Lake / Raptor Lake

Former Codename

Intel 7

GPU Lithography

Intel UHD Graphics 770

Model Name

RTX 3500 Embedded Ada Generation

HD Graphics

Generation

Quadro Ada-M

300 MHz

Base Clock

1725MHz

1450-1660 MHz (CPU dependent)

Boost Clock

2250MHz

Ring Bus

Bus Interface

PCIe 4.0 x16

Transistors

35,800 million

RT Cores

Compute Units

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.

160

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.

160

Intel

Foundry

TSMC

10 nm

Process Size

5 nm

Xe-LP (Generation 12.2)

Architecture

Ada Lovelace

Memory Specifications

System Shared

Memory Size

12GB

System Shared

Memory Type

GDDR6

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.

192bit

System Shared

Memory Clock

2250MHz

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.

432.0 GB/s

Display and Media

Decode Only

AV1 Encode/Decode

1.4a

DisplayPort Extensions

Yes

H.264 Hardware Encode/Decode

Yes

H.265 HEVC Hardware Encode/Decode

2.1

HDMI Version

Yes

Intel Quick Sync Video

7680 x 4320 @ 60Hz

Max Resolution DP

5120 x 3200 @ 120Hz

Max Resolution eDP

4096 x 2160 @ 60Hz

Max Resolution HDMI

Number of Displays Supported

Motherboard Dependent

Outputs

No outputs

Theoretical Performance

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.

144.0 GPixel/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.

360.0 GTexel/s

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.

23.04 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.

360.0 GFLOPS

0.7936 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.

23.501 TFLOPS

AI Features

Intel Deep Learning Boost on GPU

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.

256

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.

5120

L1 Cache

128 KB (per SM)

L2 Cache

48MB

15 W

TDP

100W

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

4.6

CUDA

8.9

12 (12_1)

DirectX

12 Ultimate (12_2)

Power Connectors

None

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.

6.6

Shader Model

6.7

Suggested PSU

300W