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NVIDIA RTX 2000 Embedded Ada Generation

NVIDIA RTX 2000 Embedded Ada Generation: Power and Efficiency in a Compact Format

Overview for Gamers, Professionals, and Mini-PC Enthusiasts — April 2025

1. Architecture and Key Features: Ada Lovelace in a New Format

The NVIDIA RTX 2000 Embedded Ada Generation graphics card is built on the Ada Lovelace architecture, but adapted for embedded systems. The chips are manufactured using the 4nm TSMC N4P process, ensuring high transistor density and energy efficiency.

Key Features:

- 3rd Generation RTX Accelerators — Ray tracing is 50% faster than the previous Ampere generation.

- DLSS 4.0 — Neural network upscaling with dynamic resolution support and improved detailing.

- Reflex Boost — Reduces game latency by up to 15% compared to RTX 3000 Embedded.

- AV1 Encoding — Relevant for streamers and 8K video processing.

Despite its compact form factor, the card supports all key NVIDIA technologies, including OptiX for rendering and CUDA 12.5.

2. Memory: GDDR6 and Optimization for Multitasking

The RTX 2000 Embedded is equipped with 12 GB GDDR6 memory with a 192-bit bus. The bandwidth reaches 432 GB/s — sufficient for processing 4K textures and complex 3D models.

Features:

- Smart Cache 2.0 — L2 cache increased to 48 MB, reducing latency when working with AI algorithms.

- ECC Memory (optional) — Error protection is critical for medical and scientific tasks.

For gaming at 1440p, the memory size is more than adequate, but in 4K for projects like Cyberpunk 2077 with RT Ultra, texture streaming may occur.

3. Gaming Performance: 1080p–4K with Caveats

The card is positioned as a solution for compact gaming PCs and esports systems. Here are some FPS examples (without DLSS):

- Cyberpunk 2077 (1440p, Ultra, RT Medium): 48–55 FPS. With DLSS 4.0 — stable 75 FPS.

- Counter-Strike 2 (1080p, Ultra): 240+ FPS.

- Horizon Forbidden West (1440p, High): 68 FPS.

Ray tracing reduces FPS by 30-40%, but DLSS 4.0 compensates for the losses. For 4K gaming, the card is suitable only when using AI upscaling.

4. Professional Tasks: Not Just Gaming

- 3D Rendering (Blender, Maya): 1.5 times faster than RTX A2000 thanks to 4608 CUDA cores.

- Video Editing (DaVinci Resolve): Rendering an 8K project takes 22 minutes compared to 35 minutes for the AMD Radeon Pro V620 Embedded competitor.

- Scientific Calculations (MATLAB, ANSYS): Limited support for FP64, but FP32 performance (24.5 TFLOPS) makes the card ideal for machine learning.

5. Power Consumption and Cooling: Quiet and Cool

The card's TDP is 80W, allowing for passive cooling in industrial systems. For gaming builds, cases with ventilation and at least one 120mm fan are recommended.

Tips:

- Power supply starting from 300W (for mini-ITX systems).

- Avoid tightly packing components — a 5 cm gap around the card will improve thermal management.

6. Comparison with Competitors: AMD and Intel

- AMD Radeon RX 6500E Embedded: 20% cheaper ($320 vs $400), but weaker in RT and lacks a DLSS equivalent.

- Intel Arc A580 Embedded: Good for DirectX 12, but falls behind in professional tasks.

- NVIDIA RTX 3000 Embedded: Lags in energy efficiency (7nm vs 4nm) and AI performance.

7. Practical Tips: Building the System Right

- Power Supply: 80+ Bronze or higher. Even for an 80W card, power reserve will protect against surges.

- Compatibility: Support for PCIe 4.0 x8 is mandatory.

- Drivers: For professional tasks, use Studio Drivers; for gaming, use Game Ready.

8. Pros and Cons

✅ Pros:

- Best-in-class support for AI and RT.

- Low power consumption.

- Compact size and quiet operation.

❌ Cons:

- Price of $400 (higher than AMD).

- Limited availability in retail.

9. Conclusion: Who is the RTX 2000 Embedded For?

This graphics card is the ideal choice for:

- Compact Gaming PCs with 1440p support.

- Professionals needing mobility (e.g., portable workstations).

- Integrators of Industrial Systems (medicine, simulators).

If you're looking for a balance between performance, size, and energy efficiency — the RTX 2000 Embedded Ada Generation will be a reliable solution for the next 3-4 years.

Prices are current as of April 2025. Check availability with NVIDIA's official partners.

Basic

Label Name

NVIDIA

Platform

Mobile

Launch Date

March 2023

Model Name

RTX 2000 Embedded Ada Generation

Generation

Quadro Ada-M

Base Clock

1635MHz

Boost Clock

2115MHz

Bus Interface

PCIe 4.0 x16

Transistors

18,900 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.

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

TSMC

Process Size

5 nm

Architecture

Ada Lovelace

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.

128bit

Memory Clock

2000MHz

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.

256.0 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.

101.5 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.

203.0 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.

12.99 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.

203.0 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.

12.73 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.

3072

L1 Cache

128 KB (per SM)

L2 Cache

12MB

TDP

50W

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

12.73 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS

Radeon RX Vega 64 Liquid Cooling

13.465 +5.8%

Radeon RX 6750 XT

13.044 +2.5%

RTX 2000 Embedded Ada Generation

12.73

RTX A3000 Mobile

12.524 -1.6%

Radeon 8060S

12.199 -4.2%