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NVIDIA RTX A4000 Max-Q

NVIDIA RTX A4000 Max-Q: Power and Efficiency for Professionals and Gamers

April 2025

Introduction

The NVIDIA RTX A4000 Max-Q is a compact graphics card that combines professional-level performance with energy efficiency. Designed for workstations and premium laptops, it is perfect for those who need mobility without compromises. In this article, we will explore what sets this model apart in 2025.

Architecture and Key Features

Architecture: Built on NVIDIA Blackwell — the evolution of Ada Lovelace. The TSMC 4nm process ensures high transistor density and reduced power consumption.

Unique Features:

- RTX: Third-generation hardware ray tracing for realistic lighting and shadows.

- DLSS 4.0: AI upscaling to 4K with frame generation, boosting FPS by 50-70%.

- NVIDIA Reflex: Reduces gaming latency to 15-20 ms.

- AV1 Encoding: Accelerates streaming and video rendering.

Technologies for Professionals: Supports NVIDIA Omniverse, RTX IO for fast asset loading in 3D applications.

Memory: Speed and Capacity

- Type and Capacity: 16 GB GDDR6X with a 256-bit bus.

- Bandwidth: 672 GB/s thanks to a speed of 21 Gbps per module.

- Impact on Performance: The large memory capacity allows for working with 8K textures and complex neural networks. In gaming, this means stable FPS in 4K even with high-detail mods.

Gaming Performance

The card is optimized for resolutions up to 4K. FPS examples (Ultra settings, DLSS 4.0 Quality):

- Cyberpunk 2077: 65-70 FPS at 1440p with ray tracing.

- Starfield 2: 85 FPS at 1440p.

- Call of Duty: Next War: 120 FPS at 1080p, 90 FPS at 4K.

Ray Tracing: Enabling RT reduces FPS by 25-30%, but DLSS 4.0 compensates for the losses, maintaining smoothness.

Professional Tasks

- 3D Rendering (Blender, Maya): 1.5 times faster than RTX A3000 thanks to 7680 CUDA cores.

- Video Editing (Premiere Pro): Renders an 8K project in 12 minutes (compared to 18 minutes for competitors).

- Scientific Calculations: Support for CUDA 9.0 and OpenCL 3.0 accelerates simulations in MATLAB and ANSYS.

Compatibility: Certified for Autodesk, Adobe, and SOLIDWORKS applications.

Power Consumption and Heat Generation

- TDP: 90 W — lower than desktop counterparts (140 W for RTX A4000).

- Cooling: Recommended systems with 2-3 fans or liquid cooling in compact builds.

- Cases: Suitable for SFF mini-PCs (up to 10 liters) with good ventilation.

Comparison with Competitors

- AMD Radeon Pro W6800M: Better in OpenCL tasks, but lags in rendering with RTX. Price: $1300.

- Intel Arc A770 Pro: Cheaper ($900), but weaker in professional applications by 30-40%.

- NVIDIA RTX 4070 Mobile: 10-15% higher gaming FPS, but less memory (12 GB).

Summary: The RTX A4000 Max-Q strikes a balance between gaming and professional performance.

Practical Tips

- Power Supply: A 450-500 W (80+ Gold) power supply is sufficient for a PC with this card.

- Platforms: Compatible with PCIe 5.0, but works on PCIe 4.0 without losses.

- Drivers: Use Studio Drivers for work and Game Ready for gaming.

Important: Update vBIOS to improve stability in resource-intensive tasks.

Pros and Cons

Pros:

- Energy efficiency with high performance.

- Support for all current NVIDIA AI technologies.

- Ideal for hybrid scenarios (gaming + work).

Cons:

- Price from $1400 — more expensive than gaming counterparts.

- Limited availability in retail.

Final Conclusion

The RTX A4000 Max-Q is designed for:

- Professionals: Designers, engineers, video engineers who need mobility.

- Gamers: Those who value quiet systems with 4K and ray tracing support.

It is the choice for those who do not want to compromise on power or portability. If your budget allows for $1400-1600 — this is one of the best investments in 2025.

Basic

Label Name

NVIDIA

Platform

Mobile

Launch Date

April 2021

Model Name

RTX A4000 Max-Q

Generation

Quadro Ampere-M

Base Clock

780MHz

Boost Clock

1395MHz

Bus Interface

PCIe 4.0 x16

Transistors

17,400 million

RT Cores

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.

160

Foundry

Samsung

Process Size

8 nm

Architecture

Ampere

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

1375MHz

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.

352.0 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.

111.6 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.

223.2 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.

14.28 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.

223.2 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.

13.994 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.

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.

5120

L1 Cache

128 KB (per SM)

L2 Cache

4MB

TDP

80W

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

8.6

Power Connectors

None

Shader Model

6.7

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.

Benchmarks

FP32 (float)

Score

13.994 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS

Tesla V100 SXM3 32 GB

15.357 +9.7%

RTX A4500 Mobile

14.596 +4.3%

RTX A4000 Max-Q

13.994

Radeon RX 6750 GRE

13.474 -3.7%

GRID RTX T10 8

13.117 -6.3%