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NVIDIA CMP 40HX

NVIDIA CMP 40HX: A Specialized Tool for Computing in 2025

Overview of Architecture, Performance, and Practical Value

Introduction

The NVIDIA CMP (Cryptocurrency Mining Processor) 40HX is a purpose-built solution designed for efficient cryptocurrency mining and high-load computations. However, in 2025, this card is of interest not just to miners but also to professionals who require stable computational power. In this article, we will explore who the CMP 40HX is suitable for and the tasks it can handle.

Architecture and Key Features

Architecture: The CMP 40HX is based on an updated version of the Ampere architecture, tailored for mining tasks. Unlike the gaming GPUs from the RTX series, it lacks RT cores and Tensor cores, reducing production costs.

Manufacturing Process: The card is built on Samsung's 8nm technology, providing a balance between energy efficiency and performance.

Unique Features:

- Optimization for Proof-of-Work (PoW) Algorithms: Supports Ethash, KawPow, and other algorithms.

- No Graphics Interfaces: No HDMI/DisplayPort ports, which lowers power consumption.

- Increased Reliability: Enhanced design for 24/7 operation.

Memory: Type, Capacity, and Impact on Performance

Memory Type: GDDR6 with a 256-bit bus.

Capacity: 8 GB — sufficient for mining Ethereum Classic (ETC) and similar cryptocurrencies.

Bandwidth: 448 GB/s, allowing for quick data access in hashing tasks.

Impact on Mining: High memory speed is critical for efficiency in algorithms with large DAG files. For ETC in 2025, the CMP 40HX demonstrates a hash rate of approximately 36 MH/s at 185 W.

Gaming Performance: Limitations and Real Numbers

The CMP 40HX is not intended for gaming. The lack of driver support for graphics APIs (DirectX 12, Vulkan) and RT cores makes it poorly suited for modern projects.

Test Examples (when emulated through third-party drivers):

- Cyberpunk 2077 (1080p, Ultra): ~25 FPS without ray tracing.

- Fortnite (1440p, Epic): ~40 FPS with frequent drops.

Conclusion: For gaming, opt for RTX 4060 or equivalents — the CMP 40HX even underperforms against budget gaming cards.

Professional Tasks: Editing, 3D, and Computing

Video Editing: In Adobe Premiere Pro, rendering 4K video will take 30% longer than on an RTX 4070 due to the lack of an NVENC chip.

3D Modeling: In Blender and Maya, the card handles simple scenes but requires more memory for complex projects.

Scientific Calculations: CUDA support allows using the CMP 40HX for machine learning or physical simulations, but its efficiency is lower than that of the Tesla A100.

Advice: For professional tasks, RTX 4080 or Quadro RTX 5000 would be better suited.

Power Consumption and Thermal Output

TDP: 185 W.

Cooling Recommendations:

- Use open-frame cases or mining rigs.

- Minimum requirement: 2 x 120 mm fans per card.

- Ideal temperature: below 70°C to prolong lifespan.

Power Supply Compatibility: Power supply of at least 500 W (for one card) with an 80+ Gold certification.

Comparison with Competitors

1. AMD Radeon RX 7600 XT (Mining Edition):

- Hash rate in Ethash: ~32 MH/s at 170 W.

- Price: $450 compared to $480 for CMP 40HX.

2. NVIDIA RTX 4060:

- Gaming card with a hash rate of ~28 MH/s, but with DLSS 3.5 support.

- Price: $399.

Conclusion: The CMP 40HX excels in mining but falls short in versatility.

Practical Tips

1. Power Supply: Don’t skimp — Corsair RM550x or equivalents recommended.

2. Platform: Compatible with PCIe 4.0 x16, but also works on x8/x4.

3. Drivers: Use specialized versions from NVIDIA for mining.

4. OS: Linux is preferred (increased stability for farms).

Pros and Cons

Pros:

- High mining efficiency.

- Reliability under prolonged load.

- Optimization for PoW algorithms.

Cons:

- Not suitable for gaming or graphic tasks.

- No warranty when used for mining.

- Limited driver support.

Final Conclusion: Who is the CMP 40HX Suitable For?

This card is an ideal choice for:

- Miners seeking a balance between price and efficiency.

- IT enthusiasts building computational clusters for distributed tasks.

- Labs on a budget where CU cores are used for research.

Alternative: If versatility is needed, consider the RTX 4070 or Radeon RX 7700 XT.

Price and Availability

As of April 2025, the NVIDIA CMP 40HX retails for $480. The card is supplied without a box or accessories, which reduces the cost.

Conclusion: The CMP 40HX is a specialized tool. It won't replace a gaming graphics card but will be a worthwhile investment for those who value efficiency in computing tasks.

Basic

Label Name

NVIDIA

Platform

Desktop

Launch Date

February 2021

Model Name

CMP 40HX

Generation

Mining GPUs

Base Clock

1470MHz

Boost Clock

1650MHz

Bus Interface

PCIe 3.0 x16

Transistors

10,800 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.

288

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.

144

Foundry

TSMC

Process Size

12 nm

Architecture

Turing

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.

256bit

Memory Clock

1750MHz

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.

448.0 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.

105.6 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.

237.6 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.

15.21 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.

237.6 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.

7.451 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.

2304

L1 Cache

64 KB (per SM)

L2 Cache

4MB

TDP

185W

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

7.5

Power Connectors

1x 8-pin

Shader Model

6.6

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.

Suggested PSU

450W

Benchmarks

FP32 (float)

Score

7.451 TFLOPS

Blender

Score

1320

Vulkan

Score

60353

OpenCL

Score

97694

Compared to Other GPU

FP32 (float) / TFLOPS

Arc Pro A60

8.229 +10.4%

Radeon Instinct MI8

8.028 +7.7%

CMP 40HX

7.451

Quadro RTX 4000 Max Q

7.207 -3.3%

RTX A1000

6.872 -7.8%

Blender

L40

4336 +228.5%

Tesla V100S PCIe 32 GB

2328 +76.4%

CMP 40HX

1320

Radeon RX 5600M

670 -49.2%

Radeon RX 5700M

354 -73.2%

Vulkan

Radeon RX 7700 XT

136465 +126.1%

Radeon RX 6650 XT

91134 +51%

CMP 40HX

60353

Radeon Pro 5500M

34633 -42.6%

GeForce GTX 660 Ti

15778 -73.9%

OpenCL

L20

262467 +168.7%

Radeon PRO W7800

147444 +50.9%

CMP 40HX

97694

Radeon Pro W5700

69319 -29%

Radeon Pro 5600M

48324 -50.5%