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NVIDIA GeForce RTX 4070 SUPER vs NVIDIA GeForce GTX 470

NVIDIA GeForce RTX 4070 SUPER

NVIDIA GeForce GTX 470

GPU Comparison Result

Below are the results of a comparison of NVIDIA GeForce RTX 4070 SUPER and NVIDIA GeForce GTX 470 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA GeForce RTX 4070 SUPER

Larger Memory Size: 12GB (12GB vs 1280MB)
Higher Bandwidth: 504.2 GB/s (504.2 GB/s vs 133.9 GB/s)
More Shading Units: 7168 (7168 vs 448)
Newer Launch Date: January 2024 (January 2024 vs March 2010)

Basic

NVIDIA

Label Name

NVIDIA

January 2024

Launch Date

March 2010

Desktop

Platform

Desktop

GeForce RTX 4070 SUPER

Model Name

GeForce GTX 470

GeForce 40

Generation

GeForce 400

2310MHz

Base Clock

2610MHz

Boost Clock

PCIe 4.0 x16

Bus Interface

PCIe 2.0 x16

Transistors

3,100 million

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.

Foundry

TSMC

Process Size

40 nm

Architecture

Fermi

Memory Specifications

12GB

Memory Size

1280MB

GDDR6X

Memory Type

GDDR5

192bit

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.

320bit

1313MHz

Memory Clock

837MHz

504.2 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.

133.9 GB/s

Theoretical Performance

208.8 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.

17.02 GPixel/s

584.6 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.

34.05 GTexel/s

37.42 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.

584.6 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.

136.1 GFLOPS

38.168 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.

1.067 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.

7168

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.

448

128 KB (per SM)

L1 Cache

64 KB (per SM)

48MB

L2 Cache

640KB

285W

TDP

215W

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.

N/A

3.0

OpenCL Version

1.1

OpenGL

4.6

CUDA

2.0

DirectX

12 (11_0)

Power Connectors

2x 6-pin

Shader Model

5.1

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.

Suggested PSU

550W