Home / GPU Comparison / AMD Radeon 8060S Graphics or NVIDIA GB10: What's better?

AMD Radeon 8060S Graphics

vs

NVIDIA GB10

GPU Comparison Result

Below are the results of a comparison of AMD Radeon 8060S Graphics and NVIDIA GB10 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

AMD Radeon 8060S Graphics

Higher Boost Clock: 2900 MHz (2900 MHz vs 2525 MHz)

NVIDIA GB10

Larger Memory Size: 128GB (System Shared vs 128GB)
Higher Bandwidth: 273.2GB/s (256 GB/s vs 273.2GB/s)
More Shading Units: 6144 (2560 vs 6144)
Newer Launch Date: August 2025 (January 2025 vs August 2025)

Basic

AMD

Label Name

NVIDIA

January 2025

Launch Date

August 2025

Integrated

Platform

Desktop

AMD Radeon 8060S Graphics

Model Name

GB10

Radeon 8000S

Generation

Server Blackwell

Base Clock

1665 MHz

2900 MHz

Boost Clock

2525 MHz

Integrated

Bus Interface

PCIe 5.0 x16

Transistors

Unknown

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.

384

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.

384

TSMC

Foundry

TSMC

4 nm

Process Size

3 nm

RDNA 3.5

Architecture

Blackwell

Memory Specifications

System Shared

Memory Size

128GB

System Shared LPDDR5x

Memory Type

LPDDR5X

256-bit

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.

256bit

LPDDR5x-8000

Memory Clock

1067 MHz

256 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.

273.2GB/s

Display and Media

Outputs

1x HDMI

Theoretical Performance

186 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.

121.2 GPixel/s

464 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.

969.6 GTexel/s

29.7 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.

124.1 TFLOPS

464 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.

15.51 TFLOPS

14.85 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.

31.651 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.

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.

6144

L1 Cache

256 KB (per SM)

L2 Cache

50 MB

TDP

Unknown

2.1

OpenCL Version

3.0

4.6

OpenGL

CUDA

10.1

DirectX

None

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.

6.8

Shader Model

Suggested PSU

200 W