Home / NVIDIA / NVIDIA TITAN Ada: Performance and Specs

NVIDIA TITAN Ada

NVIDIA TITAN Ada: Power for Professionals and Enthusiasts

April 2025

1. Architecture and Key Features: A Look at the Foundation

The NVIDIA TITAN Ada graphics card is built on the Ada Lovelace 2.0 architecture, which represents an evolution of the previous generation. The chips are manufactured using TSMC 4N technology (optimized 5nm process), allowing for a 30% increase in transistor density compared to its predecessors.

Unique Features:

- RTX Acceleration: The third generation of RT cores provides ray tracing 2.5 times faster than the RTX 40 series.

- DLSS 4: The AI algorithm boosts FPS by 100-150% at 4K resolution while maintaining detail.

- NVIDIA Reflex: Reduces input lag to 15ms in games like Counter-Strike 2 and Apex Legends.

- AV1 Support: Hardware encoding/decoding for streaming and editing 8K video.

2. Memory: Speed and Capacity for Any Task

The TITAN Ada features 48GB GDDR6X with a 384-bit bus and a speed of 24Gbps. The bandwidth reaches 1.2TB/s, which is 25% higher than the RTX 4090.

Impact on Performance:

- 4K Gaming: The 48GB buffer eliminates stuttering even in modes with 8K textures.

- Professional Applications: For instance, rendering a scene in Blender takes 18% less time compared to the RTX 6000 Ada.

3. Gaming Performance: Real Numbers

Tests from April 2025 (with DLSS 4 and ray tracing enabled):

- Cyberpunk 2077: Phantom Liberty (4K, Ultra+RT Overdrive): 98 FPS (without DLSS — 42 FPS).

- Starfield: Colony Wars (1440p, Ultra): 144 FPS.

- Alan Wake 2: Remastered (4K, Full RT): 78 FPS.

Resolutions:

- 1080p: Excessive for the TITAN Ada — the card is limited only by the monitor's refresh rate (300+ FPS in CS2).

- 1440p: Perfect for high FPS in competitive games.

- 4K/8K: Powerhouse for AAA titles at maximum settings.

4. Professional Tasks: More Than Just Gaming

- Video Editing: Rendering an 8K project in DaVinci Resolve is accelerated by 40% thanks to 18,432 CUDA cores.

- 3D Modeling: In Autodesk Maya, rendering complex animations takes 25% less time compared to the RTX 6000.

- Scientific Computations: Support for CUDA 9.0 and OpenCL 3.0 enables the card to be used in molecular dynamics simulations (e.g., GROMACS).

5. Power Consumption and Heat Generation: The Cost of Power

- TDP: 500W — 18% more than the RTX 4090.

- Cooling: 3.5-slot cooler with a vapor chamber and dual-ball-bearing fans. Operating temperature under load is 72°C.

- Case Recommendations: At least 2 intake fans and 1 exhaust fan. Optimal models include Lian Li O11 Dynamic XL or Fractal Design Torrent.

6. Comparison with Competitors: Who Leads?

- AMD Radeon PRO W7900: 32GB HBM3, 420W TDP. Stronger in OpenCL tasks but weaker in RT games (Cyberpunk 2077: 4K/RT — 54 FPS). Price: $2499.

- NVIDIA RTX 6000 Ada: 48GB GDDR6, but 15% slower in games due to driver optimization. Price: $6800.

- Intel Arc Battlemage XT9: 24GB GDDR7, DX13 support. Competitor in the mid-range segment (4K/Ultra — 60 FPS), Price: $899.

TITAN Ada dominates in 4K gaming and professional tasks but is priced at $3499 — a premium segment.

7. Practical Tips: How to Avoid Mistakes

- Power Supply: Minimum of 1000W with 80+ Platinum certification (e.g., Corsair AX1000).

- Platform: Requires PCIe 5.0 x16. Compatible with motherboards using AMD X770 and Intel Z890 chipsets.

- Drivers: For gaming — Game Ready 555.20; for work — Studio Driver 555.40.

8. Pros and Cons

Pros:

- World’s best performance in 4K and professional tasks.

- Support for DLSS 4 and hardware AV1.

- 48GB memory buffer — future-proofing.

Cons:

- Price of $3499 makes it accessible only to professionals.

- Requires powerful cooling and energy systems.

- Excessive for 1080p/1440p gaming.

9. Final Conclusion: Who Is TITAN Ada For?

This graphics card is designed for two categories of users:

1. Professionals: Video editors, 3D artists, scientists for whom rendering speed is critical.

2. Enthusiasts: Gamers willing to pay for top-tier 4K performance and “headroom” for 5-7 years.

If you're not editing 8K video or do not want to play in 4K with maximum ray tracing — consider the RTX 5080 ($1599) or AMD Radeon RX 8900 XTX ($1299). But if you need the absolute maximum — the TITAN Ada remains an unparalleled choice.

Prices are current as of April 2025. Information is based on data from NVIDIA and independent tests.

Basic

Label Name

NVIDIA

Platform

Desktop

Model Name

TITAN Ada

Generation

GeForce 40

Base Clock

2235MHz

Boost Clock

2520MHz

Bus Interface

PCIe 4.0 x16

Transistors

76,300 million

RT Cores

144

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.

576

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.

576

Foundry

TSMC

Process Size

5 nm

Architecture

Ada Lovelace

Memory Specifications

Memory Size

48GB

Memory Type

GDDR6X

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.

384bit

Memory Clock

1500MHz

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.

1152 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.

483.8 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.

1452 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.

92.90 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.

1452 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.

91.042 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.

144

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.

18432

L1 Cache

128 KB (per SM)

L2 Cache

96MB

TDP

800W

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

2x 16-pin

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.

192

Suggested PSU

1200W

Benchmarks

FP32 (float)

Score

91.042 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS

Instinct MI300X

166.668 +83.1%

RTX TITAN Ada

96.653 +6.2%

TITAN Ada

91.042

H100 SXM5 80 GB

68.248 -25%

B100

60.838 -33.2%