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NVIDIA RTX 3500 Mobile Ada Generation

NVIDIA RTX 3500 Mobile Ada Generation: Power and Efficiency in Mobile Format

April 2025

1. Architecture and Key Features: Ada Lovelace 2.0

The NVIDIA RTX 3500 Mobile graphics card is built on the updated Ada Lovelace 2.0 architecture, which is an evolution of the original Ada. The chips are manufactured using the 4 nm TSMC process, allowing for a 20% increase in transistor density compared to the first version of Ada. This has resulted in improved performance with lower power consumption.

Key Technologies:

- RTX Acceleration: 3rd generation ray tracing with enhanced noise reduction algorithms.

- DLSS 3.5: AI Super Resolution now works even in games without native support for the technology.

- FidelityFX Compatibility: Support for open standards like AMD FidelityFX Super Resolution (FSR 3.0) for cross-platform optimization.

- Ada Reflex: Input latency reduction of up to 15% in esports titles.

These features make the RTX 3500 Mobile a versatile solution for both gaming and creative tasks.

2. Memory: Speed and Capacity

The card is equipped with 12 GB GDDR6X memory with a 192-bit bus, providing a bandwidth of 432 GB/s. This is a 25% increase compared to the RTX 3060 Mobile, and it is sufficient for handling 4K textures in games or rendering complex 3D scenes.

Memory Features:

- Smart Access: Dynamic resource allocation between the CPU and GPU in systems with Ryzen 7000/8000 series.

- L3 Cache increased to 48 MB, speeding up tasks with "heavy" engines like Unreal Engine 5.5.

For most games at 1440p, 12 GB is a future-proof reserve, but in professional tasks (e.g., rendering in Blender), memory capacity can become a limiting factor for extremely complex projects.

3. Gaming Performance: From Full HD to 4K

The RTX 3500 Mobile delivers impressive results in modern games:

- Cyberpunk 2077: Phantom Liberty (1440p, RT Ultra, DLSS 3.5): 58-62 FPS.

- GTA VI (1080p, Ultra, FSR 3.0 Quality): 85 FPS.

- Starfield: Enhanced Edition (4K, Medium, DLSS Performance): 45 FPS.

Ray tracing reduces FPS by 30-40%, but DLSS 3.5 compensates for the losses, adding up to 20 frames. In games without RT, the card easily handles 1440p@60 FPS on ultra settings.

Recommendation: For comfortable 4K gaming, it’s best to use DLSS/FSR in Quality or Balanced mode.

4. Professional Tasks: Not Just for Gamers

With 3072 CUDA cores and support for OpenCL 3.0, the RTX 3500 Mobile is suitable for:

- Video Editing: Rendering 8K projects in DaVinci Resolve is 25% faster than with the RTX 3060 Mobile.

- 3D Modeling: In Blender, the BMW Render test completes in 4.2 minutes (compared to 6.1 minutes with the previous generation).

- Machine Learning: The 4th generation Tensor Cores accelerate neural network training in TensorFlow by 18%.

For mobile workstations, it offers an excellent balance between price and performance.

5. Power Consumption and Heat Dissipation: Efficiency First

The card has a TDP of 90 W, but thanks to the 4 nm process, peak power consumption in games rarely exceeds 75 W.

Cooling Recommendations:

- Laptops with three heat pipes and two fans (e.g., ASUS ROG Zephyrus M16 2025).

- Using cooling pads during prolonged workloads.

- Regular thermal paste replacement (every 1.5-2 years).

The card is not suitable for ultra-thin laptops — the minimum system thickness should be at least 18 mm.

6. Comparison with Competitors: AMD and Intel

AMD Radeon RX 7700M XT:

- Comparable price ($1100-$1300), but about 15% weaker in ray tracing tasks.

- Pros: Better energy efficiency in Vulkan games.

Intel Arc A770M:

- Cheaper ($900-$1000), but drivers are still unstable for professional applications.

Conclusion: The RTX 3500 Mobile outperforms its competitors thanks to DLSS 3.5 and stable driver support.

7. Practical Tips: How to Choose a System

- Laptop Power Supply: At least 180 W for models with Intel Core i7/i9 14th generation processors.

- Compatibility: Requires PCIe 5.0 x8, but works on PCIe 4.0 with minimal losses.

- Drivers: Update via GeForce Experience — in April 2025, NVIDIA released optimizations for the "Horizon Forbidden West PC Port."

Important: Check the laptop screen refresh rate — models with 144-165 Hz are optimal for the RTX 3500 Mobile.

8. Pros and Cons

Pros:

- DLSS 3.5 and RTX performance.

- Support for professional applications.

- Energy efficiency.

Cons:

- Price starting from $1200 (only GPU in a laptop).

- Limited availability in ultrabooks.

9. Final Conclusion: Who Is This Card For?

The RTX 3500 Mobile Ada Generation is the ideal choice for:

- Gamers who want to play at 1440p with maximum settings.

- Designers and video editors needing mobility without compromises.

- Students studying AI and 3D modeling.

With laptops starting from $1500, this is one of the most balanced GPUs on the market, combining NVIDIA's innovations with the practicality of a mobile format.

Basic

Label Name

NVIDIA

Platform

Mobile

Launch Date

March 2023

Model Name

RTX 3500 Mobile Ada Generation

Generation

Quadro Ada-M

Base Clock

1110MHz

Boost Clock

1545MHz

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.

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

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.

98.88 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.

247.2 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.

15.82 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.

247.2 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.

15.504 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

48MB

TDP

100W

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

15.504 TFLOPS

Blender

Score

5323

Compared to Other GPU

FP32 (float) / TFLOPS

Radeon RX 6800

16.493 +6.4%

Tesla V100 DGXS 32 GB

15.983 +3.1%

RTX 3500 Mobile Ada Generation

15.504

Quadro RTX 8000 Passive

14.631 -5.6%

Tesla T40 24 GB

14.092 -9.1%

Blender

GeForce RTX 5090

15026.3 +182.3%

RTX 3500 Mobile Ada Generation

5323

GeForce RTX 2070

2020.49 -62%

Radeon RX 6800S

1064 -80%

GeForce GTX 980 Ti

552 -89.6%