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NVIDIA RTX 4000 Mobile Ada Generation

NVIDIA RTX 4000 Mobile Ada Generation: Power and Innovation in a Mobile Format

April 2025

Introduction

The NVIDIA RTX 4000 Mobile Ada Generation is the flagship mobile graphics card for gamers and professionals, combining the advanced Ada Lovelace architecture with optimization for laptops. In this article, we will explore how it performs in gaming, rendering, and scientific tasks, and who should pay attention to it.

1. Architecture and Key Features

Ada Lovelace Architecture: A Revolution in Miniature

The card is built on TSMC's 4 nm process, providing increased transistor density (up to 35 billion) and energy efficiency. The Ada Lovelace architecture brings:

- DLSS 4.0 — neural network scaling with AI frame support, boosting FPS by 2–3 times in 4K.

- 3rd Generation RTX Accelerators — ray tracing is now 50% faster than in the RTX 3000 Mobile.

- Reflex and Broadcast — reduced latency in games and improved streaming.

- Support for FidelityFX Super Resolution 3.0 — cross-platform technology from AMD, optimized for hybrid systems.

2. Memory: Speed and Capacity

GDDR6X and 16 GB: Future-Proofing

The card features 16 GB of GDDR6X memory with a 256-bit bus, providing a bandwidth of 768 GB/s (compared to 384 GB/s in the RTX 3080 Mobile). This is critical for:

- 4K Gaming with RTX — for example, Cyberpunk 2077: Phantom Liberty requires up to 12 GB of memory.

- Professional Tasks — rendering complex 3D scenes in Blender requires a minimum of 10–12 GB.

- Multitasking — simultaneous work with video editing software and neural network models.

3. Gaming Performance

4K Without Compromise

In tests from April 2025, the card demonstrates:

- Cyberpunk 2077 (with RTX Ultra + DLSS 4.0): 68 FPS in 4K, 89 FPS in 1440p.

- Starfield: Enhanced Edition: 76 FPS in 4K (DLSS 4.0), 120 FPS in 1440p.

- Apex Legends: 144 FPS in 4K (maximum settings).

Ray Tracing: The Price of Beauty

Activating RTX reduces FPS by 30–40%, but DLSS 4.0 compensates for losses. For instance, in The Witcher 4 (1440p, RTX High) without DLSS — 45 FPS, with DLSS 4.0 — 78 FPS.

4. Professional Tasks

CUDA, OptiX, and Studio Drivers

- Video Editing: Rendering an 8K project in DaVinci Resolve is accelerated by 40% compared to the RTX 3080 Mobile.

- 3D Modeling: Particle simulation in Autodesk Maya takes 25% less time.

- Scientific Calculations: Support for CUDA 12.5 and OpenCL 3.0 allows for efficient work with machine learning algorithms (e.g., training models in TensorFlow).

5. Power Consumption and Thermal Management

TDP 140 Watts: Balancing Power and Temperature

The RTX 4000 Mobile is adapted for slim gaming laptops (thickness from 19 mm) but requires advanced cooling:

- Chassis Recommendations: Systems with 3–4 heat pipes and a couple of fans (e.g., ASUS ROG Zephyrus M16 2025).

- Thermal Interface: Using liquid metal reduces temperatures by 5–7°C.

- Operating Modes: In driver settings, you can limit TDP to 100 Watts to reduce noise.

6. Comparison with Competitors

AMD Radeon RX 7900M XT: The Battle of Giants

- AMD Advantages: 18 GB GDDR6, support for FidelityFX Super Resolution 3.0, laptop prices starting at $2200 (compared to $2500 for NVIDIA).

- NVIDIA Advantages: Better optimization for ray tracing, DLSS 4.0, wider support for professional software.

- Intel Arc Xe9: Cheaper ($1800), but lags behind in 4K performance by 25–30%.

7. Practical Tips

How to Choose a Laptop with RTX 4000 Mobile?

- Power Supply: At least 280 Watts for full performance.

- Platforms: It's better to choose models based on Intel Core i9-14900HX or AMD Ryzen 9 8945HS to avoid bottlenecks.

- Drivers: Regularly update Studio drivers for stable operation in professional applications.

8. Pros and Cons

Pros:

- Outstanding performance in 4K and with RTX.

- 16 GB GDDR6X — future-proof for upcoming games and tasks.

- Support for DLSS 4.0 and AI tools.

Cons:

- Laptop prices start at $2500.

- Noise under full load even in premium chassis.

- Limited model selection (currently available only in top series by ASUS, MSI, Razer).

9. Final Conclusion: Who is RTX 4000 Mobile Suitable For?

This graphics card is an ideal choice for:

- Gamers looking to play in 4K with maximum settings without being tethered to a desktop.

- Video editors and 3D artists needing a mobile workstation.

- Engineers and scientists working with resource-intensive calculations in the field.

If your budget allows for an investment in a laptop priced at $2500–3000, the RTX 4000 Mobile Ada Generation will be a reliable companion for the next 3–4 years.

Basic

Label Name

NVIDIA

Platform

Mobile

Launch Date

March 2023

Model Name

RTX 4000 Mobile Ada Generation

Generation

Quadro Ada-M

Base Clock

1290MHz

Boost Clock

1665MHz

Bus Interface

PCIe 4.0 x16

Transistors

35,800 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.

232

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.

232

Foundry

TSMC

Process Size

5 nm

Architecture

Ada Lovelace

Memory Specifications

Memory Size

12GB

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.

192bit

Memory Clock

2250MHz

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.

432.0 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.

133.2 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.

386.3 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.

24.72 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.

386.3 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.

25.214 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.

7424

L1 Cache

128 KB (per SM)

L2 Cache

48MB

TDP

110W

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

8.9

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

25.214 TFLOPS

Blender

Score

5163

Compared to Other GPU

FP32 (float) / TFLOPS

Radeon RX 7700

32.589 +29.2%

GeForce RTX 4070

29.733 +17.9%

RTX 4000 Mobile Ada Generation

25.214

RTX A4500

23.177 -8.1%

GeForce RTX 4060 Ti 16 GB

22.501 -10.8%

Blender

GeForce RTX 5090

15026.3 +191%

RTX 4000 Mobile Ada Generation

5163

GeForce RTX 2070

2020.49 -60.9%

Radeon RX 6800S

1064 -79.4%

GeForce GTX 980 Ti

552 -89.3%