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NVIDIA GeForce RTX 3070 Mobile vs AMD Radeon 660M

NVIDIA GeForce RTX 3070 Mobile

AMD Radeon 660M

GPU Comparison Result

Below are the results of a comparison of NVIDIA GeForce RTX 3070 Mobile and AMD Radeon 660M video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA GeForce RTX 3070 Mobile

Larger Memory Size: 8GB (8GB vs System Shared)
Higher Bandwidth: 448.0 GB/s (448.0 GB/s vs System Dependent)
More Shading Units: 5120 (5120 vs 384)

AMD Radeon 660M

Higher Boost Clock: 1900MHz (1560MHz vs 1900MHz)
Newer Launch Date: January 2022 (January 2021 vs January 2022)

Basic

NVIDIA

Label Name

AMD

January 2021

Launch Date

January 2022

Mobile

Platform

Integrated

GeForce RTX 3070 Mobile

Model Name

Radeon 660M

GeForce 30 Mobile

Generation

Rembrandt

1110MHz

Base Clock

1500MHz

1560MHz

Boost Clock

1900MHz

PCIe 4.0 x16

Bus Interface

PCIe 4.0 x8

17,400 million

Transistors

13,100 million

RT Cores

Compute Units

160

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.

Samsung

Foundry

TSMC

8 nm

Process Size

6 nm

Ampere

Architecture

RDNA 2.0

Memory Specifications

8GB

Memory Size

System Shared

GDDR6

Memory Type

System Shared

256bit

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

1750MHz

Memory Clock

SystemShared

448.0 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.

System Dependent

Theoretical Performance

124.8 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

249.6 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

15.97 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

249.6 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.

91.20 GFLOPS

15.651 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

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.

5120

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 SM)

L1 Cache

128 KB per Array

4MB

L2 Cache

2MB

115W

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

3.0

OpenCL Version

2.0

4.6

OpenGL

4.6

8.6

CUDA

12 Ultimate (12_2)

DirectX

12 Ultimate (12_2)

None

Power Connectors

None

6.6

Shader Model

6.5

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.