NVIDIA Quadro RTX 4000 Max Q

NVIDIA Quadro RTX 4000 Max Q

NVIDIA Quadro RTX 4000 Max Q is a Professional video accelerator from NVIDIA. It began to be released in May 2019. The GPU has a boost frequency of 1380MHz. It also has a memory frequency of 1625MHz. Its characteristics, as well as benchmark results, are presented in more detail below.

Basic

Label Name
NVIDIA
Platform
Professional
Launch Date
May 2019
Model Name
Quadro RTX 4000 Max Q
Generation
Quadro Mobile
Base Clock
780MHz
Boost Clock
1380MHz
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
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.
40
Transistors
13,600 million
RT Cores
40
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.
320
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
L1 Cache
64 KB (per SM)
L2 Cache
4MB
Bus Interface
PCIe 3.0 x16
Foundry
TSMC
Process Size
12 nm
Architecture
Turing
TDP
80W

Memory Specifications

Memory Size
8GB
Memory Type
GDDR6
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
Memory Clock
1625MHz
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.
416.0 GB/s

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.
88.32 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.
220.8 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.
14.13 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.
220.8 GFLOPS
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.
7.064 TFlops

Miscellaneous

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
OpenCL Version
3.0
OpenGL
4.6
DirectX
12 Ultimate (12_2)
CUDA
7.5
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.
64
Shader Model
6.6

FP32 (float)

7.064 TFlops

Blender

1878

OctaneBench

43

Compared to Other GPU

SiliconCat Rating

371
Ranks 371 among all GPU on our website
FP32 (float)
Radeon Instinct MI8
AMD, December 2016
8.027 TFlops
Radeon RX 6700S
AMD, January 2022
7.458 TFlops
Quadro RTX 4000 Max Q
NVIDIA, May 2019
7.064 TFlops
6.787 TFlops
Tesla M40 24 GB
NVIDIA, November 2015
6.562 TFlops
Blender
GeForce RTX 4090
NVIDIA, September 2022
12577
2912
Quadro RTX 4000 Max Q
NVIDIA, May 2019
1878
Tesla M40 24 GB
NVIDIA, November 2015
589
Tesla K80
NVIDIA, November 2014
258
OctaneBench
GeForce RTX 4050 Mobile
NVIDIA, January 2023
254
P104 100
NVIDIA, December 2017
124
Quadro RTX 4000 Max Q
NVIDIA, May 2019
43
GeForce GTX 1080 Max Q
NVIDIA, June 2017
10