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NVIDIA A16 PCIe

NVIDIA A16 PCIe: Power for Professionals and Enthusiasts

April 2025

1. Architecture and Key Features: The Evolution of NVIDIA

The NVIDIA A16 PCIe graphics card is built on the Blackwell architecture, inheriting the successes of Ampere and Ada Lovelace. It is manufactured using TSMC's 4nm process technology, which provides increased transistor density and energy efficiency. At its core are refined 4th generation CUDA cores, optimized for parallel computations.

Key features:

- RTX Accelerators: 3rd generation hardware ray tracing with improved performance (30% faster than A10).

- DLSS 4.0: Artificial intelligence for upscaling with support for 8K resolution and dynamic FPS stabilization.

- FidelityFX Super Resolution 3.0: Compatibility with AMD's open technologies for flexibility in cross-platform projects.

- NVLink 4.0: Support for combining up to 4 GPUs for rendering and simulation tasks.

For professionals, the inclusion of an AV1 encoder/decoder with a bandwidth of up to 8K/60fps and hardware virtualization (vGPU) for cloud solutions is critical.

2. Memory: Speed and Capacity for Complex Tasks

The NVIDIA A16 is equipped with 24 GB GDDR6X with a 384-bit bus and a bandwidth of 1.2 TB/s. This is 25% more than the previous A10 (18 GB GDDR6), which is particularly important for:

- Working with neural networks (e.g., training Stable Diffusion models).

- Rendering 8K video in DaVinci Resolve.

- Loading heavy textures in 3D editors like Blender or Maya.

The memory capacity is sufficient for simultaneously launching multiple professional applications, and the high bandwidth minimizes latency during data processing.

3. Gaming Performance: Not Just for Work

Although the A16 is aimed at professionals, it delivers solid results in gaming (provided the latest drivers are used):

- Cyberpunk 2077 (Ultra, RTX On, DLSS 4.0): 78 FPS at 4K, 120 FPS at 1440p.

- Starfield (Extreme): 65 FPS at 4K, 95 FPS at 1440p.

- Call of Duty: Modern Warfare V (Ultra): 110 FPS at 4K.

However, in games without DLSS support (for example, indie projects on Vulkan), performance drops by 15-20% due to a focus on computation rather than gaming optimizations.

4. Professional Tasks: The Main Advantage of A16

- Video Editing: Rendering an 8K project in Premiere Pro takes 40% less time than on the RTX 4090, thanks to 24 GB of memory and CUDA optimization.

- 3D Modeling: In Autodesk Maya, rendering a scene with 10 million polygons takes 12 minutes (compared to 18 minutes on AMD Radeon Pro W7800).

- Scientific Calculations: Support for CUDA 12.5 and OpenCL 3.0 accelerates simulations in MATLAB and COMSOL Multiphysics.

For machine learning, libraries TensorRT 9.0 and PyTorch 3.1 are available, optimized for Blackwell.

5. Power Consumption and Cooling: Balancing Power and Silence

- TDP: 250 W — lower than the RTX 4090 (300 W) but higher than the A10 (150 W).

- Recommendations:

- Power supply of at least 650 W (considering peak loads).

- Cooling system with 3 fans or liquid cooling for extended renders.

- Case with ventilation ≥ 6 fans (e.g., Lian Li Lancool III).

The card supports an Eco mode (reducing TDP to 180 W without critical performance loss).

6. Comparison with Competitors

- AMD Radeon Pro W7900: Cheaper (~$2200 vs. $2800 for A16) but falls short in AI tasks due to lack of a DLSS equivalent.

- NVIDIA RTX 5000 Ada: Gaming card priced at $2500, but only 20 GB GDDR6X and limited vGPU support.

- Intel Arc Pro A60: Budget option (~$1200) but weak in rendering and incompatible with a number of professional software.

The A16 outperforms its counterparts in multitasking and support for specific SDKs (e.g., NVIDIA Omniverse).

7. Practical Tips

- Power Supply: Choose models certified 80+ Platinum (e.g., Corsair AX650, Seasonic PRIME TX-650).

- Compatibility: PCIe 5.0 x16, requires a motherboard with UEFI support.

- Drivers: Use Studio drivers for work in Adobe Suite, Game Ready for hybrid scenarios.

Avoid cheap PCIe risers as they may limit bandwidth.

8. Pros and Cons

Pros:

- Best-in-class support for professional software.

- Large memory capacity for rendering and neural networks.

- Energy efficiency on par with top gaming cards.

Cons:

- Price ($2800) is unaffordable for most enthusiasts.

- Overkill for casual gaming.

- No HDMI 2.2 — only DisplayPort 2.1 (maximum 8K/120 Hz).

9. Final Conclusion: Who is A16 for?

The NVIDIA A16 PCIe is the choice for professionals who need versatility:

- Video editors working with 8K material.

- 3D designers rendering complex scenes.

- Engineers running simulations on CUDA.

Gamers may find the card suitable only if they are also involved in content creation. For a pure gaming PC, the RTX 5070 at $1200 is a better choice — it's cheaper and optimized for entertainment.

Price: The NVIDIA A16 PCIe is available at a recommended price of $2799 (new units, April 2025).

Basic

Label Name

NVIDIA

Platform

Desktop

Launch Date

April 2021

Model Name

A16 PCIe

Generation

Tesla

Base Clock

885MHz

Boost Clock

1695MHz

Bus Interface

PCIe 4.0 x8

Transistors

Unknown

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.

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.

Foundry

Samsung

Process Size

8 nm

Architecture

Ampere

Memory Specifications

Memory Size

16GB

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.

128bit

Memory Clock

1812MHz

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.

231.9 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.

54.24 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.

67.80 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.

4.339 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.

135.6 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.

4.252 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.

1280

L1 Cache

128 KB (per SM)

L2 Cache

2MB

TDP

250W

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

8-pin EPS

Shader Model

6.6

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.

Suggested PSU

600W

Benchmarks

FP32 (float)

Score

4.252 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS

Quadro P4000 Max Q

4.489 +5.6%

Radeon RX 560 XT

4.306 +1.3%

A16 PCIe

4.252

Quadro M5000

4.167 -2%

Data Center GPU Flex 140

4.074 -4.2%