Home / GPU Comparison / AMD Radeon 840M or NVIDIA GeForce GTX 1080: What's better?

AMD Radeon 840M

vs

NVIDIA GeForce GTX 1080

GPU Comparison Result

Below are the results of a comparison of AMD Radeon 840M and NVIDIA GeForce GTX 1080 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

AMD Radeon 840M

Higher Boost Clock: 2800-2900 MHz (2800-2900 MHz vs 1733MHz)
Newer Launch Date: February 2025 (February 2025 vs May 2016)

NVIDIA GeForce GTX 1080

Larger Memory Size: 8GB (Shared system memory vs 8GB)
Higher Bandwidth: 320.3 GB/s (System memory dependent vs 320.3 GB/s)
More Shading Units: 2560 (256 vs 2560)

Basic

Intel

Label Name

NVIDIA

February 2025

Launch Date

May 2016

Integrated

Platform

Desktop

Krackan Point / Gorgon Point

Former Codename

4 nm

GPU Lithography

AMD Radeon 840M

Model Name

GeForce GTX 1080

Radeon 800M Series

Generation

GeForce 10

Base Clock

1607MHz

2800-2900 MHz

Boost Clock

1733MHz

Integrated

Bus Interface

PCIe 3.0 x16

Transistors

7,200 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.

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

TSMC

Foundry

TSMC

4 nm

Process Size

16 nm

RDNA 3.5

Architecture

Pascal

Memory Specifications

Shared system memory

Memory Size

8GB

System shared

Memory Type

GDDR5X

Dual-channel system memory, platform dependent

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

System memory dependent

Memory Clock

1251MHz

System memory 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.

320.3 GB/s

Display and Media

Yes

AMD FreeSync

Encode/Decode

AV1 Encode/Decode

Adaptive-Sync, HBR3, UHBR10

DisplayPort Extensions

Encode/Decode

H.264 Hardware Encode/Decode

Encode/Decode

H.265 HEVC Hardware Encode/Decode

No hardware support

H.266 VVC Hardware Encode/Decode

2.3

HDCP Version

2.1

HDMI Version

Intel Quick Sync Video

7680x4320 @ 60Hz

Max Resolution DP

7680x4320 @ 60Hz

Max Resolution HDMI

1080p60 8bpc MPEG2, 1080p60 8bpc VC1, 1080p786 8/10bpc VP9, 2160p196 8/10bpc VP9, 4320p49 8/10bpc VP9, 1080p1200 8bpc H.264, 2160p300 8bpc H.264, 4320p75 8bpc H.264, 1080p786 8/10bpc H.265, 2160p196 8/10bpc H.265, 4320p49 8/10bpc H.265, 1080p960 8/10bpc AV1, 2160p240 8/10bpc AV1, 4320p60 8/10bpc AV1

Max Video Decode Bandwidth

1080p630 8bpc H.264, 1440p373 8bpc H.264, 2160p175 8bpc H.264, 1080p630 8bpc H.265, 1440p373 8bpc H.265, 2160p175 8bpc H.265, 4320p43 8bpc H.265, 1080p864 8/10bpc AV1, 1440p513 8/10bpc AV1, 2160p240 8/10bpc AV1, 4320p60 8/10bpc AV1

Max Video Encode Bandwidth

Number of Displays Supported

HDMI 2.1, DisplayPort 2.1, USB-C DisplayPort Alt Mode; device dependent

Outputs

1x DVI
1x HDMI 2.0
3x DisplayPort 1.4a

Yes

USB Type-C DisplayPort Alternate Mode

Miracast

Wireless Display

Theoretical Performance

22.4-23.2 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.

110.9 GPixel/s

44.8-46.4 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.

277.3 GTexel/s

2.87-2.97 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.

138.6 GFLOPS

89.6-92.8 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.

277.3 GFLOPS

1.48 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.

8.696 TFLOPS

AI Features

Intel Deep Learning Boost on GPU

Up to 50 TOPS

NPU TOPS

Up to 59 TOPS

Processor Overall TOPS

Miscellaneous

Available

AMD SmartAccess Memory

16 total / 16 usable

Native PCIe Lanes

PCIe 4.0

PCI Express Version

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.

2560

L1 Cache

48 KB (per SM)

L2 Cache

2MB

Shared with processor; platform dependent

TDP

180W

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

2.1

OpenCL Version

3.0

4.6

OpenGL

4.6

CUDA

6.1

12 Ultimate (12_2)

DirectX

12 (12_1)

None

Power Connectors

1x 8-pin

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.

6.7

Shader Model

6.4

Suggested PSU

450W