NVIDIA RTX PRO 4000 Blackwell
vs
NVIDIA Quadro P600
vs
GPU Comparison Result
Below are the results of a comparison of
NVIDIA RTX PRO 4000 Blackwell
and
NVIDIA Quadro P600
video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Higher Boost Clock: 2617 MHz (2617 MHz vs 1557MHz)
- Larger Memory Size: 24GB (24GB vs 2GB)
- Higher Bandwidth: 672.0GB/s (672.0GB/s vs 64.13 GB/s)
- More Shading Units: 8960 (8960 vs 384)
- Newer Launch Date: March 2025 (March 2025 vs February 2017)
Basic
NVIDIA
Label Name
NVIDIA
March 2025
Launch Date
February 2017
Desktop
Platform
Professional
RTX PRO 4000 Blackwell
Model Name
Quadro P600
Blackwell PRO W
Generation
Quadro
1590 MHz
Base Clock
1329MHz
2617 MHz
Boost Clock
1557MHz
PCIe 5.0 x16
Bus Interface
PCIe 3.0 x16
45.6 billion
Transistors
3,300 million
70
RT Cores
-
280
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.
-
280
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.
24
TSMC
Foundry
Samsung
5 nm
Process Size
14 nm
Blackwell 2.0
Architecture
Pascal
Memory Specifications
24GB
Memory Size
2GB
GDDR7
Memory Type
GDDR5
192bit
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
1750 MHz
Memory Clock
1002MHz
672.0GB/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.
64.13 GB/s
Theoretical Performance
251.2 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.
24.91 GPixel/s
732.8 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.
37.37 GTexel/s
46.90 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.
18.68 GFLOPS
732.8 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.
37.37 GFLOPS
45.962
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.
1.22
TFLOPS
Miscellaneous
70
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.
3
8960
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.
384
128 KB (per SM)
L1 Cache
48 KB (per SM)
48 MB
L2 Cache
1024KB
140W
TDP
40W
1.4
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
12 Ultimate (12_2)
DirectX
12 (12_1)
10.1
CUDA
6.1
1x 16-pin
Power Connectors
None
96
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.
16
6.8
Shader Model
6.4
300 W
Suggested PSU
200W
Benchmarks
FP32 (float)
/ TFLOPS
RTX PRO 4000 Blackwell
45.962
+3667%
Quadro P600
1.22
OpenCL
RTX PRO 4000 Blackwell
202069
+1707%
Quadro P600
11181
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