NVIDIA RTX A1000
vs
NVIDIA GeForce RTX 4060

vs
NVIDIA RTX A1000 vs NVIDIA GeForce RTX 4060 graphics card comparison

GPU Comparison Result

NVIDIA RTX A1000 vs GeForce RTX 4060: What's More Important - Compactness or Speed

NVIDIA RTX A1000 can easily be mistaken for a stripped-down alternative to the GeForce RTX 4060. Both graphics cards feature 8 GB of GDDR6 memory, a 128-bit bus, and connect via PCIe 4.0 x8. However, the similarities end there with just a few lines of specifications. The RTX 4060 is designed for gaming and resource-intensive home applications, while the RTX A1000 is meant for workstations where the graphics card needs to fit in a single slot, consume no more than 50 watts, and perform reliably with professional software.

Therefore, the question is not which model is faster: the RTX 4060 wins by a large margin. It's much more important to understand in what systems the advantages of the RTX A1000 truly justify its lower performance.

Key Differences

Parameter NVIDIA RTX A1000 GeForce RTX 4060
Architecture Ampere Ada Lovelace
CUDA Cores 2304 3072
FP32 Performance around 6.7 TFLOPS around 15 TFLOPS
Video Memory 8 GB GDDR6 8 GB GDDR6
Memory Bus 128 bits 128 bits
Power Consumption 50 W 115 W
Form Factor Low Profile, 1 slot usually 2 slots
Primary Use Case Professional workstations Gaming, rendering, home PC

The table highlights the main contradiction in this comparison: the RTX A1000 is nearly three times more energy-efficient and significantly more compact, but the RTX 4060 has more than double the computing power.

Why the RTX 4060 is Significantly Faster

The RTX A1000 is based on the Ampere architecture and features 2304 CUDA cores, second-generation RT cores, and third-generation Tensor cores. This setup allows for hardware ray tracing, CUDA calculations, and 3D graphics work; however, the 50 W power limit restricts clock speeds.

The RTX 4060 is built on the newer Ada Lovelace architecture. It has more computing blocks, higher clock speeds, and more advanced ray tracing and neural network processing units. The theoretical FP32 performance is around 15 TFLOPS compared to 6.7 TFLOPS for the RTX A1000.

This difference also persists under real workloads. In rendering, effect processing, neural network tasks, and gaming, the RTX 4060 typically falls into a different performance class. The same amount of video memory doesn't significantly change things here: 8 GB dictates how much data can be housed in the GPU but doesn’t compensate for the difference in computational resources.

Gaming: RTX A1000 is Hindered by Power Limit

The RTX 4060 is designed for gaming at a resolution of 1920 × 1080. It supports ray tracing, DLSS Super Resolution, and frame generation. In less demanding projects, the card can also handle 1440p, although 8 GB of video memory may already limit maximum texture settings.

The RTX A1000 can technically also run modern games and supports DirectX 12 Ultimate. The issue is not compatibility but performance. Its single-slot cooling and 50 W power consumption prevent it from coming close to the RTX 4060 in heavy projects.

Considering the RTX A1000 for gaming makes sense only under strict constraints:

  • The case only supports low-profile single-slot cards;
  • The power supply has no separate connector for the graphics card;
  • Power consumption and heat are more important than frame rates;
  • Games are used as a secondary rather than primary load.

In all other cases, the RTX 4060 is the more rational choice. It is not only faster but also offers features that the Ampere generation lacks, including hardware-based DLSS frame generation.

Where the RTX A1000 Shows Its Advantages

The RTX A1000 is designed for compact workstations. It receives all its power from the PCIe slot, occupies a single slot, and is available in a low-profile format. This allows it to be installed in thin office computers or specialized systems where standard gaming graphics cards physically cannot fit.

Another feature is the professional NVIDIA RTX Enterprise drivers. For home users, the difference with GeForce drivers may be negligible. In a corporate environment, certification for CAD and engineering software, predictable behavior after updates, and a long support cycle are important.

The RTX A1000 is also equipped with four Mini DisplayPort connectors. This is convenient for workplaces with multiple monitors, dispatch complexes, medical equipment, and information systems. The RTX 4060 also supports multi-monitor configurations, but its layout and output set are primarily aimed at typical desktop PCs.

Working with Video and 3D Graphics

Professional RTX indexing does not automatically mean that the A1000 is faster in work applications. In Blender, video editors, and other CUDA-enabled applications, the RTX 4060 often holds the advantage thanks to its more powerful GPU.

Ada Lovelace also features a modern hardware encoder with AV1 support. For editing, recording gameplay, and streaming, the RTX 4060 is more functional. The RTX A1000 makes sense not as the fastest accelerator but as a compact professional card with a certified software environment.

Conclusion

The GeForce RTX 4060 is the choice for gaming, home rendering, editing, and a versatile computer. It is more than twice as powerful in FP32, supports frame generation, and features a modern media engine.

The RTX A1000 serves a different purpose. It packs 8 GB of memory, hardware ray tracing, and professional drivers into a single-slot card consuming 50 watts. Compactness comes at the cost of performance, but in a thin workstation, alternatives in such a format are limited.

The RTX A1000 is not a weaker version of the RTX 4060. It is a specialized tool for systems where size, power consumption, and driver stability are more important than maximum speed.

Advantages

  • Newer Launch Date: April 2024 (April 2024 vs May 2023)
  • Higher Boost Clock: 2460MHz (1462MHz vs 2460MHz)
  • Higher Bandwidth: 272.0 GB/s (192.0 GB/s vs 272.0 GB/s)
  • More Shading Units: 3072 (2304 vs 3072)

Basic

NVIDIA
Label Name
NVIDIA
April 2024
Launch Date
May 2023
Desktop
Platform
Desktop
RTX A1000
Model Name
GeForce RTX 4060
Quadro Ampere
Generation
GeForce 40
727MHz
Base Clock
1830MHz
1462MHz
Boost Clock
2460MHz
PCIe 4.0 x8
Bus Interface
PCIe 4.0 x8
8,700 million
Transistors
Unknown
18
RT Cores
24
72
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.
96
72
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.
96
Samsung
Foundry
TSMC
8 nm
Process Size
5 nm
Ampere
Architecture
Ada Lovelace

Memory Specifications

8GB
Memory Size
8GB
GDDR6
Memory Type
GDDR6
128bit
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
1500MHz
Memory Clock
2125MHz
192.0 GB/s
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.
272.0 GB/s

Display and Media

4x mini-DisplayPort 1.4a
Outputs
1x HDMI 2.1
3x DisplayPort 1.4a

Theoretical Performance

46.78 GPixel/s
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.
118.1 GPixel/s
105.3 GTexel/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.
236.2 GTexel/s
6.737 TFLOPS
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.
15.11 TFLOPS
105.3 GFLOPS
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.
236.2 GFLOPS
6.872 TFLOPS
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.
14.808 TFLOPS

Miscellaneous

18
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.
24
2304
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
128 KB (per SM)
L1 Cache
128 KB (per SM)
2MB
L2 Cache
24MB
50W
TDP
115W
1.3
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
3.0
OpenCL Version
3.0
4.6
OpenGL
4.6
8.6
CUDA
8.9
12 Ultimate (12_2)
DirectX
12 Ultimate (12_2)
None
Power Connectors
1x 12-pin
32
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.
48
6.7
Shader Model
6.7
250W
Suggested PSU
300W

Benchmarks

FP32 (float) / TFLOPS
RTX A1000
6.872
GeForce RTX 4060
14.808 +115%
Blender
RTX A1000
1305.5
GeForce RTX 4060
3410 +161%
Vulkan
RTX A1000
49526
GeForce RTX 4060
93644 +89%
OpenCL
RTX A1000
53439
GeForce RTX 4060
102044 +91%