Home / GPU Comparison / NVIDIA B200 or NVIDIA B300: What's better?

NVIDIA B200

vs

NVIDIA B300

GPU Comparison Result

Below are the results of a comparison of NVIDIA B200 and NVIDIA B300 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA B300

Higher Boost Clock: 2600 MHz (975 MHz vs 2600 MHz)
Larger Memory Size: 144GB (90GB vs 144GB)
Newer Launch Date: September 2025 (January 2024 vs September 2025)

Basic

NVIDIA

Label Name

NVIDIA

January 2024

Launch Date

September 2025

Desktop

Platform

Desktop

B200

Model Name

B300

Server Blackwell

Generation

Server Blackwell

700 MHz

Base Clock

1665 MHz

975 MHz

Boost Clock

2600 MHz

PCIe 5.0 x16

Bus Interface

PCIe 5.0 x16

104 billion

Transistors

104 billion

640

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.

640

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.

640

TSMC

Foundry

TSMC

5 nm

Process Size

5 nm

Blackwell

Architecture

Blackwell Ultra

Memory Specifications

90GB

Memory Size

144GB

HBM3e

Memory Type

HBM3e

4096bit

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.

4096bit

2000 MHz

Memory Clock

2000 MHz

4.10TB/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.

4.10TB/s

Display and Media

No outputs

Outputs

No outputs

Theoretical Performance

23.40 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.

62.40 GPixel/s

624.0 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.

1664.0 GTexel/s

159.7 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.

426.0 TFLOPS

19.97 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.

1.664 TFLOPS

Miscellaneous

160

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.

160

20480

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.

20480

256 KB (per SM)

L1 Cache

256 KB (per SM)

50 MB

L2 Cache

50 MB

1000W

TDP

1400W

3.0

OpenCL Version

3.0

10.0

CUDA

10.3

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.

1400 W

Suggested PSU

1800 W

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