Category: PC Builds

Are you planning to build your machine learning PC but need help figuring out where to start? Look no further! Building your machine learning PC can be daunting, but with the right guidance, it can be a rewarding experience. A machine learning PC is designed for running machine learning models and algorithms. It requires powerful hardware components such as a high-end graphics processing unit (GPU), a large amount of memory (RAM), and a fast central processing unit (CPU).

Before you start building your machine learning PC, you need to determine your budget and the requirements of your machine learning projects. The budget will determine the type and quality of the components you can use. The requirements of your machine learning projects will determine the amount of memory, GPU, and CPU processing power you need. Once you have determined your budget and requirements, you can start selecting the components for your machine learning PC. The following sections will guide you through building your machine learning PC, from choosing the parts to assembling the PC.

Hardware Components

When building a machine learning PC, choosing the right hardware components will help you achieve optimal performance is essential. Here are the key components you should consider:

CPU

The CPU is the brain of your machine learning PC. When choosing a CPU, you should look for a processor with a high core count and clock speed. Intel and AMD offer a range of CPUs that are suitable for machine learning tasks.

GPU

The GPU is the most important component of a machine learning PC. NVIDIA is the leading provider of GPUs for machine learning, and their GeForce and Quadro series are popular choices. When choosing a GPU, you should look for one with many CUDA cores and memory.

RAM

RAM is important for storing data during machine learning tasks. You should choose a RAM that has a high frequency and low latency. 16GB of RAM is the minimum requirement for most machine learning tasks, but you may need more depending on the size of your datasets.

Storage

Storage is important for storing your large data sets and models. You should choose an SSD for faster read and write speeds. A 500GB or 1TB SSD is recommended for most machine learning tasks.

Motherboard

The motherboard is the backbone of your machine learning PC. It would help if you chose a motherboard that is compatible with your CPU and GPU. Look for a motherboard that has a high number of PCIe slots for adding additional GPUs.

Power Supply

The power supply is vital for providing enough power to your machine learning PC. It would help if you chose a power supply with high wattage and 80+ certified for efficiency.

Case

The case is vital for keeping your machine learning PC cool and protected. It would help if you chose a case with good airflow and enough space for your components.

Cooling

Cooling is essential for keeping your machine learning PC running smoothly. It would be best if you chose a cooling solution suitable for your CPU and GPU. Liquid cooling is recommended for high-end components.

GPU Selection

When building a machine learning PC, selecting the right GPU is crucial. This section will discuss the different types of GPUs available, as well as their features and specifications.

NVIDIA GPUs

NVIDIA GPUs are the most popular choice among machine learning enthusiasts and the main choice for building high end computers. They are known for their high performance and excellent support for popular deep learning frameworks like TensorFlow and PyTorch. Some of the most popular NVIDIA GeForce RTX GPUs for machine learning include the 2080 Ti and the Titan RTX.

AMD GPUs

While NVIDIA GeForce RTX GPUs are the most popular choice for machine and deep learning models, AMD GPUs are also worth considering. AMD GPUs are known for their high memory bandwidth, which can benefit specific machine learning tasks and other AI workloads. However, they are less well-supported than a Nvidia graphics card regarding deep learning frameworks.

GPU Memory

When selecting a GPU for machine learning, it is essential to consider the amount of memory it has. The more memory a GPU has, the larger the models it can handle. Most modern GPUs come with at least 8GB of memory, but for larger models, consider a GPU with 16GB or more.

Tensor Cores

Tensor Cores are a specialized type of core found in certain NVIDIA GPUs. They are designed to accelerate matrix operations, a key component of many machine learning algorithms. If you plan on working with large models or datasets, a GPU with Tensor Cores can significantly speed up your model training times.

CUDA Cores

CUDA Cores are another important feature when selecting a GPU for machine learning. CUDA Cores are specialized processing units that are designed to accelerate parallel computations. The more CUDA Cores a GPU has, the faster it can perform certain machine learning tasks.

In conclusion, selecting the right GPU is critical when building a machine learning PC. NVIDIA GPUs are the most popular choice, but AMD GPUs are also worth considering. When selecting a GPU, consider its memory, Tensor Cores, and CUDA Cores to ensure it can handle your machine learning demanding workloads.

CPU Selection

When building a machine learning PC, selecting the right CPU is crucial for achieving optimal performance. Here are some factors to consider when selecting a CPU.

Intel CPUs

Intel CPUs are known for their strong single-threaded performance, making them a popular choice for workstation and for machine learning applications. The Intel Xeon W and Intel Core i9 processors are excellent machine learning options. The Xeon W is higher budget, designed for workstation use and offers high core counts and support for ECC memory, while the Core i9 is a more affordable option with a high clock speed and good single-threaded performance.

AMD CPUs

AMD CPUs offer better multi-threaded performance than Intel CPUs, making them an excellent choice for machine learning applications that require parallel processing. The AMD Ryzen Threadripper Pro is a popular choice for machine and deep learning workstations, offering high core counts and support for PCIe 4.0. The AMD Ryzen 9 is a more affordable for deep learning workstation PCs, with good multi-threaded performance and a high clock speed.

CPU Cores

The number of CPU cores is important when selecting a CPU for machine learning. More cores allow for more parallel processing, greatly improving data science performance. However, more cores also mean a higher price tag. A CPU with at least eight cores is recommended for the PC build capable of most machine learning applications.

Clock Speed

Clock speed is another important factor when selecting a CPU for machine learning. A higher clock speed means faster single-threaded performance, which is important for some machine learning applications. However, a higher clock speed also means more heat and power consumption and can come at a premium price. For most machine learning applications, a CPU with a clock speed of at least 3.5 GHz is recommended.

Memory Selection

When building a machine learning PC, selecting the right memory is crucial for optimal performance. Here are key factors to consider when selecting memory for your machine learning PC build.

RAM Speed

The speed of your RAM can significantly impact the performance of your machine learning PC. Faster RAM allows quicker data transfer between the CPU and RAM, improving the speed of data processing and training. When selecting RAM, look for options with a higher clock speed, such as DDR4-3200 or DDR4-3600.

DDR4 Memory

DDR4 memory is the current standard for PC memory and is the recommended option for machine learning PCs. DDR4 memory provides faster data transfer rates and improved power efficiency compared to older DDR3 memory. When selecting DDR4 memory, consider the capacity you need. For most machine learning applications, 16GB or 32GB of DDR4 memory should be sufficient.

VRAM

In addition to system memory, your machine learning PC will require dedicated video memory (VRAM) if you use a GPU for training. VRAM is used to store data that the GPU is processing. When selecting a GPU, consider the amount of VRAM it has. A GPU with at least 8GB of VRAM is recommended for most machine learning applications.

Selecting the right memory is crucial for building a powerful machine learning PC. Consider the speed of your RAM, the capacity of your DDR4 memory, and the amount of VRAM in your GPU when making your selection. By making informed choices, you can ensure that your machine learning PC is optimized for performance and can handle even the most demanding applications.

Storage Selection

When building a machine learning PC, the storage space is an important consideration. You need to ensure that your storage solution is fast, reliable, and able to store your data and applications. This section will discuss the different types of storage available and which one you should choose for your machine learning PC.

SSD Selection

Solid-state drives (SSDs) are faster and more reliable than traditional hard drives and disk drives (HDDs). They use flash memory to store data, which means they have no moving parts. This makes them less prone to failure and faster than HDDs. When selecting an SSD or hard drive for your machine learning PC, you should consider the following factors:

• Capacity: SSDs come in different capacities, ranging from 128GB to 4TB or more. Choose an SSD with a capacity that meets your needs.
• Interface: SSDs connect to your motherboard via a SATA or PCIe interface. PCIe SSDs are faster than SATA SSDs but are also more expensive.
• Brand: Choose a reputable brand when selecting an SSD. Some of the most popular brands include Samsung, Crucial, and Western Digital.

NVMe SSDs

NVMe (Non-Volatile Memory Express) SSDs are even faster than traditional SSDs. They use the PCIe interface and the NVMe protocol to deliver faster read and write speeds. When selecting an NVMe SSD for your machine learning PC, you should consider the following factors:

• Capacity: NVMe SSDs come in different capacities, ranging from 256GB to 2TB or more. Choose an NVMe SSD with a capacity that meets your needs.
• Interface: NVMe SSDs use the PCIe interface, which is faster than the SATA interface used by traditional SSDs.
• Brand: Choose a reputable brand when selecting an NVMe SSD. The most popular brands include Samsung, Western Digital, and Corsair.

HDD Selection

Traditional hard disk drives (HDDs) are slower and less reliable than SSDs. However, they are also cheaper and have larger capacities. When selecting an HDD for your machine learning PC, you should consider the following factors:

• Capacity: HDDs come in different capacities, ranging from 1TB to 10TB or more. Choose an HDD with a capacity that meets your needs.
• Interface: HDDs connect to your motherboard via a SATA interface. They are slower than SSDs but are also cheaper.
• Brand: Choose a reputable brand when selecting an HDD. Some of the most popular brands include Western Digital, Seagate, and Toshiba.

When selecting storage for your machine, deep learning workstation, or PC, you should consider your capacity, speed, and reliability needs. SSDs and NVMe SSDs are faster and more reliable than HDDs but are also more expensive. HDDs are cheaper and have larger capacities but are slower and less reliable. Choose the storage solution that meets your needs and budget.

Motherboard Selection

When building a machine learning PC, choosing the right motherboard is crucial. It is the backbone of your system and determines the compatibility of all your other components. Here are some factors to consider when selecting a motherboard for your machine learning PC.

PCIE Slots

PCIE slots are essential for any machine learning PC as they provide the bandwidth for high-speed data transfer between your GPU and CPU. When selecting a motherboard, ensure it has at least one PCIE 3.0 x16 slot to accommodate your graphics card. If you use multiple GPUs, look for a motherboard with multiple PCIE slots, preferably with PCIE 3.0 x16 bandwidth.

Form Factor

The form factor of your motherboard determines the size and shape of the board. The most common form factors are ATX, Micro-ATX, and Mini-ITX. ATX motherboards are the largest and offer the most expansion slots and features. Micro-ATX motherboards are smaller and have fewer expansion slots but are still suitable for most machine learning PC builds. Mini-ITX motherboards are the smallest and have limited expansion capabilities but are perfect for compact builds.

When selecting a motherboard, consider the form factor of your case and the size of most tasks your other components. For example, if you plan on using a large CPU cooler or multiple GPUs, you may need an ATX motherboard to accommodate them.

In summary, when selecting a motherboard for your machine learning PC, ensure it has the necessary PCIE slots and form factor to accommodate your processor and other components. Consider the size of your case and other components, and choose a motherboard that offers the features and expansion capabilities you need.

Software Components

You must have the right software components to build a machine learning PC. These include the operating system, machine learning frameworks, libraries, and package managers. Here’s what you need to know about each of them.

Operating System

The operating system you choose can affect the performance of your machine learning PC. Most machine learning frameworks and libraries work well with Linux-based operating systems, such as Ubuntu, Debian, or CentOS. You can also choose to use Windows 10 or macOS, but you may need to install additional software or drivers to get everything working smoothly.

Machine Learning Frameworks

Machine learning frameworks are essential for building and training machine learning models. Some popular frameworks include TensorFlow, PyTorch, and Keras. TensorFlow is an open-source platform for building and training machine learning models, while PyTorch is a popular deep learning framework that provides dynamic computation graphs. Keras is a high-level neural networks API that is easy to use and supports both TensorFlow and Theano backends.

Libraries

Libraries are collections of pre-written code that you can use to build machine learning models. Some popular libraries include Scikit-Learn, OpenCV, Numpy, Matplotlib, and Pandas. Scikit-Learn is a machine learning library for Python that provides simple and efficient tools for data mining and data analysis. OpenCV is a computer vision library that provides real-time computer vision and machine learning capabilities. Numpy is a Python programming language library that supports large, multi-dimensional arrays and matrices. Matplotlib is a plotting library for Python that provides high-quality 2D and 3D plots. Pandas is a library for data manipulation and analysis.

Package Managers

Package managers are tools that make it easy to install and manage software packages. Some popular package managers include Anaconda, pip, and Conda. Anaconda is a package manager, an environment manager, and a Python and R programming languages distributor. Pip is a package manager for Python that allows you to install and manage software packages easily. Conda is a package and environment manager that allows you to create virtual environments for different projects and manage the dependencies of your projects.

In summary, to build a machine learning PC, you need to have the right software components, including the operating system, machine learning frameworks, libraries, and package managers. Choosing the right components can affect the performance of your machine learning PC, so it’s essential to do your research and choose wisely.

Building the PC

Building a machine learning PC can be daunting, but with the right guidance, you can easily build one that suits your needs. This section will guide you through building your machine for ai deep learning, PC, from assembly to installation, computing power, and configuration, and finally, testing.

Assembly

Before assembling the PC, you must ensure that you have all the necessary hardware components. You should have a motherboard, CPU, RAM, GPU, storage device, power supply, and a computer case. Once you have all the components, you can start the assembly process.

1. First, attach the CPU to the motherboard, ensuring the pins are aligned correctly.
2. Install the RAM into the motherboard’s memory slots, ensuring that the side clips click into place.
3. Install the GPU into the PCIe slot on the motherboard, ensuring it clicks into place.
4. Install the storage device into the appropriate slot in the computer case.
5. Attach the motherboard to the computer case, ensuring it is securely fastened.
6. Connect the power supply to the motherboard and other components.

Installation and Configuration

Once you have assembled the PC, you must install and configure the necessary software components. You should install the operating system, drivers, and machine learning libraries.

1. Install the operating system of your choice, such as Windows, Linux, or macOS.
2. Install the drivers for your hardware components, such as the GPU driver.
3. Install machine learning libraries like TensorFlow, PyTorch, or Keras.

Testing

After installing and configuring the software components, you should test the system to ensure that almost everything works correctly. You can run benchmark tests to evaluate the system’s performance.

1. Run benchmark tests like TensorFlow’s benchmark suite to evaluate the system’s performance.
2. Ensure that the GPU is utilized correctly by running a GPU stress test.
3. Verify that the machine learning libraries are working correctly by running sample code.

Building a machine learning PC is a challenging but rewarding task. Following the steps outlined above, you can build a powerful machine learning PC that meets your needs. Remember to take your time and ensure you have all the necessary hardware and software components before starting the building process.

Conclusion

Building a machine learning PC can be daunting, but with the right knowledge and tools, it can be a rewarding experience over a decade. Here are some key takeaways to keep in mind when building your machine learning PC:

• Choose the right GPU: The GPU is the most important component of a machine learning PC. Make sure you choose a GPU that is optimized for machine learning tasks.
• Consider your CPU and RAM: While the GPU is the most important component, you still need a good CPU and enough RAM to support your machine learning tasks.
• Invest in good cooling: Machine learning tasks can be very demanding on your PC, so investing in good cooling is crucial to ensure your PC runs smoothly and doesn’t overheat.
• Choose the right power supply: Make sure you choose a power supply that can handle the power requirements of your machine learning PC.
• Remember storage: Machine learning tasks can require a lot of storage, so make sure you choose a fast storage option with enough capacity.

Overall, building a machine learning PC can be a great way to save money and get the maximum performance that you need for your machine learning tasks. With the right components and a little knowledge, you can build a machine learning PC that can handle even the most demanding tasks.

As a graphics designer, animator, architect, or 3D artist, you need a powerful computer to carry out certain tasks. But how powerful your PC needs to be depends on the kind of workload you’re carrying out. For 3D animation or 2D animation, you need something beefier. And animation computers are usually not cheap.

If we want to build a desktop for animation, we’d need something potent, powerful, and within the price range that we want. But can we really meet all those criteria?

We’ll find out in this article as we show you how to build a desktop computer meant for 3D animation and modeling.

Starting from Scratch: Building a Computer for Animation

Believe it or not, it’s possible to build a desktop for animation that’s affordable but powerful at the same time. When we say powerful, we are referring to a PC that can carry out animation tasks without difficulty.

Here’s a short cheat sheet of the kind of hardware components you need for building a decent desktop for animation. This also applies to window shopping for a laptop for animation too.

CPU and RAM Combination

CPU and RAM need to be fast enough to power through all the animation software, 3D modeling software, and other software support for animation projects.

You’ll need at least 32GB DDR4 RAM sticks with a frequency of 3600MHz up to 4000MHz. For processors, you’ll need at least an Intel Core i7 9th generation or 10th generation, or an AMD Ryzen processor equivalent to the Intel Core i7,

GPU or Graphics Card

Building a computer for animation requires a dedicated graphics card. While you could power through 3D animation projects with an integrated graphics card, it will be relatively slower than having a dedicated graphics card.

Popular software such as Adobe After Effects have yet to fully take advantage of GPU rendering, but it doesn’t mean you should be ignoring your GPU. Nvidia graphics cards have better Adobe After Effects support than AMD graphics card, so we recommend getting an Nvidia Geforce RTX 3060 at the very least.

Storage Space

Animators, modelers, and graphic designers need a lot of storage space. Period.

Not only are you dealing with renders, but you also have to store project files, assets, and other resources. These take up a sizeable amount of your hard drive, especially when you’re doing major projects.

You’ll need at least two storage drives. One of them should be an SSD or solid state drive to host your software and operating system, and the other should be a traditional HDD to house all the files and renders.

Your combination would probably be at 1TB NVMe SSD and 2TB/4TB HDD. Of course, if you can afford more capacity for SSD, then go for more.

Motherboard

While the motherboard doesn’t really affect the overall build, you’re here to consider how the motherboard supports all the other hardware components listed above.

An Intense Debate: Mac or PC?

Between getting a desktop computer for animation and a Macbook, which one’s actually better for 3D animation, modeling, and graphics design?

The practical answer here is this: it depends.

It depends on:

How big is your budget?

Apple products are always going to be expensive but you’re getting premium pieces of hardware. The specs of the current generation Macbook Air and Macbook Pro can easily compete against gaming PCs that run old graphics cards or CPUs.

Gaming laptops are similarly priced as Macbooks, depending on their GPU and CPU. Laptops running RTX 3000-series or their AMD equivalent combined with an Intel Core i7 or i9 processor or their AMD equivalent will cost the same, if not more, as a Macbook.

A gaming PC will slightly be more affordable than the two, but you don’t really have mobility. Unless you plan on working when you’re traveling, then your best option is to get a desktop PC for 3D animation and more.

How big are your projects?

The best computer that you need for animation and modeling depends on how big your projects are. Even if you’re just starting out, you should be future-proofing your build by thinking about the size of your animation work.

Your own computer should be prepared to handle the biggest animation workloads possible even if you’re just not there yet.

How mobile do you have to be?

Mobility is something to consider when you’re doing animation work outside of your home. A portable laptop is the answer for mobility issues, or an Apple Macbook. You’ll need a laptop with dedicated GPU, a decent battery life, and a processor capable of CPU rendering.

You will never get the right answer from places like Reddit because you’ll only hear biased inputs from their proponents.

Fact of the matter is, a desktop computer will always be more powerful than a Macbook. There’s just no denying that. Apple may be proud of their CPUs and iGPUs, and they’re just as capable of running the heaviest animation software possible, but the power is just limited.

Think of it this way. It’s like arguing who defeats who: Batman or Superman?

However, if your desktop computer for animation has lower specs than a Macbook, then the latter is going to be better.

Most people would often go for a gaming PC or a laptop as their go-to system for their animation workstation computer. But a gaming PC just offers the most flexibility and versatility. An animation PC can be built and upgraded on a whim without difficulty. Laptops can’t be upgraded, save for their RAMs and storage but even then it’s not that much.

Sample Builds From The Internet

The following builds were curated from the Internet and come in various price ranges. This is how you’d probably assemble your desktop computer for 3D animation and more.

These builds are more than capable of doing other tasks such as video editing, graphics design, and other animation tasks.

Having said that, let’s go over what makes a decent computer for animation and how much you’re more likely to spend with each build.

Uncapped Budget a.k.a Money Is Not An Issue

Estimated cost: About $4,500 to $5,000

Ideal for: Established professionals in the industry who need a powerful animation workstation computer at home

• CPU: AMD R9 7950X
• Graphics Card: ASUS TUF GeForce RTX 4090
• Motherboard: Asus Prime X670-P
• RAM: G.Skill Trident Z5 64GB RAM Kit
• Storage 1: 1TB Samsung 970 Pro M.2 SSD
• Storage 2: 2x 10TB Seagate IronWolf HDDs (for RAID-1 redundancy)

All righty, first up we have this insanely powerful computer if budget is not an issue. We’re talking about having enough disposable income that you have no second thoughts when buying any of the hardware components above.

You’re getting an AMD Ryzen 9 7950X with 16-cores and 32-threads. Unlike the other CPUs down the line, the AMD Ryzen 9 7950X runs at full speed and on max power. You’re also getting the beastly RTX 4090 and 64GB of RAM.

1TB SSD and up to 20TB of HDD storage to house all the files for your animation projects. The CPU and GPU cost more than half of the entire rig. Of course, every other component can still be tweaked, like the casing, cooling system, and power supply. But even then,

Cost-Effective Build

Estimated cost: $700+ at the very least

Ideal for: animators who’re just starting or those who just want a decent computer for animation without breaking the bank

• CPU: AMD R5 5600G
• Graphics Card: Gigabyte GeForce GTX 1650 D6 OC
• Motherboard: ASRock B550M PRO4
• RAM: Patriot Viper Steel DDR4 16GB (2 x 8GB) 3200MHz
• Storage: Western Digital 500GB WD Blue SA510 SATA

Above, we have an all-out computer build if you’re not concerned about the budget. This next build is for people on the other side of the coin. The budget starts off at the $700 mark, so there’s enough room for a couple of upgrades down the line.

The build that we have takes advantage of the AMD processors, a steady amount of RAM, and a mid-tier graphics card, and a decent storage capacity. This is already a powerful gaming PC as it stands, and it’s more than capable of running most animation software and video editing software.

A Balanced Mid-Range Build

Estimated cost: $1,200+

Ideal for: People who want the best computer with competitive hardware components without the risk of overspending.

• CPU: AMD R5 7600X
• Graphics Card:MSI Gaming GeForce GTX 1660 Super
• Motherboard: MSI PRO X670-P WiFi ProSeries Motherboard
• RAM: G.Skill Trident Z5 RGB Series
• Storage 1: Western Digital 500GB WD Blue SA510 SATA
• Storage 2: Seagate IronWolf Pro 4TB NAS Internal Hard Drive HDD

Right here is what we’d consider the Goldilocks build. Not too expensive but not too cheap, but just right.

We have a decent combination of AMD CPU, a high-end GPU, and enough storage capacity for bigger animation projects. The SSD can be upgraded to 1TB when you have more budget, and you can expand the HDD storage.

This desktop PC will roughly cost you about $1,200 at least, making it a solid animation PC and gaming PC at the same time.

How to Choose the Best Laptop for Animation

Choosing the best laptop as an alternative for animation PC or animation desktop PC is ideal if you’re constantly traveling or if your office doesn’t have a spare computer for animation.

Majority of the gaming laptops you see in the market are more than capable of running any animation software, but they’ll probably be more expensive than building a gaming PC.

Your only point of concern here would be battery life. Now it’s not recommended to render animation projects when you’re running on battery life since the laptop switches to the integrated GPU for rendering. You’ll blow through the entire battery in 30 minutes or less, and it’s not ideal.

The best laptops for gaming and doing animation work are those with at least an Intel Core i7 processor and at least an Nvidia GeForce RTX 3060 to carry out complex animations. You could also go down in budget if you go for the RTX 2000-series laptops.

3D animation, modeling, and rendering are daunting in their own right. A PC, workstation, or even a laptop needs to have enough processing power to carry out 3D-related workloads.

But that’s easier said than done since your machine needs to run powerful components. We’re talking about mid range processors, graphics cards, RAM, and even storage devices. Let’s not forget about the peripherals too.

If you want a laptop for Blender or for any 3D software, then you’ll need something that’s just as powerful.

In this article, we’ll be talking about the best computer for Blender, or laptop for that matter. We’re also going to give you a small cheat sheet at the final section of the article if you want to build your own computer.

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What is Blender?

Blender is a free and open-source 3D Creation Suite, as defined by their company. The software is capable of running the entire 3D pipeline, from modeling to rigging to motion tracking to game creation and so on.

Blender is one of the best 3D software suite for creative professionals and studios, so you can imagine just how powerful this engine is. But Blender users will need a high end machine to run this software smoothly.

What’s The Best PC or Laptop For Blender?

The list is not arranged in any particular order and is a curation of different recommendations from users and studios.

HP Omen Obelisk

A Premium Prebuilt Gaming PC for the Serious Blender User

Specs

• Intel Core i7-9700K
• NVIDIA(R) GeForce(R) RTX 2070 SUPER(TM)
• 16 GB
• 1 TB
• Windows 10 Pro

Now if you want to go down the expensive route, you might want to consider the HP Omen Obelisk, a beast of a gaming PC that could last you for a good five or ten years without upgrading a single thing.

Don’t get us wrong. You’re paying close to $2,000 for this machine, but you’re getting the best of the best. For starters, you have a 9th generation Intel Core i7 processor combined with the Nvidia GeForce RTX 2070 Super. Complimenting this build is 16GB of RAM and 1TB of SSD storage space, with room for upgrade. Their gaming laptops under the same name also have the same specs.

You can use this PC for gaming, video editing, and yes, for Blender or any other 3D software. Unfortunately, there are no other configurations but you can upgrade individual computer hardware like the CPU, GPU, and RAM if you want more power.

Acer Nitro 50 N50-600

Compact and Powerful Blender PC

Specs

• Intel Core i7-9700 Processor
• NVIDIA GeForce RTX 2060
• ‎16 GB DDR4
• ‎1 TB Mechanical Hard Drive
• ‎Windows 10 Home

Much like HP Omen, Acer Nitro is another recognizable brand when it comes to gaming PCs and laptops. The Acer Nitro 50 N50-600 is on this list for a couple of reasons.

First, we have the processor and graphics card combo. The Acer Nitro 50 N50-600 packs an Intel Core i7 9th generation processor and an Nvidia GeForce RTX 2060 graphics card. Both extremely powerful then, and still as powerful as the latest generations now.

Second, you’re getting computer hardware to complement the CPU/GPU tandem. You’re getting 16GB of RAM, 512GB SSD, and 1TB Mechanical Hard Drive (HDD).

And lastly, these are all upgradeable. Mind you, the CPU and GPU won’t need any replacement for the foreseeable future. You can upgrade to more storage space and more RAM.

For the price you’re paying, this PC does it all.

SkyTech Blaze

A Perfect Option for Creatives On A Budget

Specs

• Ryzen 5 1600 6-Core 3.2 GHz (3.6 GHz Turbo)
• NVIDIA GeForce GTX 1050 Ti 4GB GDDR5
• 8GB DDR4 2400 Gaming Memory
• 500 GB- 1TB 7200 RPM HDD
• Windows 10 Home

GPU rendering is a major point of consideration when it comes to choosing PCs or laptops with the right computer hardware. But some of the major Nvidia GPUs are quite expensive, so what choice do you have?

Well, the Skytech Blaze is first on the list and is perfectly capable of running simple tasks on Blender. There are several upgraded configurations to choose from, but the basic configuration should be a good start.

And for less than $1,000, you already got yourself a good CPU and one of the midrange Nvidia graphics cards that enable GPU rendering. With the Ryzen 5 1600 processor, you can easily run Blender.

Acer Predator Orion 3000

Specs

• 11th Generation Intel Core i7-11700F
• NVIDIA GeForce RTX 3070
• 16 GB DDR4 RAM
• 512GB SSD + 1TB HDD
• Windows 10 Home

If you want something powerful that looks the part, then the Acer Predator Orion is a no-brainer of a choice.

The Acer Predator Orion comes with 5 different configurations. The basic config runs an 11th-generation Intel Core i7 processor and RTX 2060 graphics card and will cost you about $1,700. The ultimate configuration runs an 12th-generation Intel Core i7 and an Nvidia GeForce RTX 3080, one of the most powerful Nvidia GPUs in the market right now. The RTX 3080 configuration will cost you about $2,500.

This PC is one of the best for running Blender and the more intensive 3D software apps. If you’re running more resource intensive tasks, then upgrading the RAM should be a priority. Or you could always go for the Intel Core i9 if you’re underwhelmed by the i7.

iBUYPOWER Pro Gaming PC Trace 4

A Budget Friendly Alternative to the SkyTech Blaze

Specs

• AMD Ryzen 5 3600 3.6GHz (4.2GHz Max Turbo)
• NVIDIA GT 730 2GB
• 8 GB DDR4 RAM
• 240GB SSD
• Windows 10 Home

Another budget-friendly alternative is the iBUYPOWER Pro Gaming PC Trace 4, hovering just a smidge below the $1,000 price point. And just like the SkyTech Blaze 4, you’re getting what you pay for.

The iBUYPOWER Pro Gaming PC Trace 4 is nothing to scoff at. You get an AMD Ryzen 5 3600 processor, an Nvidia GT 730 2GB graphics card, and about 8GB of DDR4 RAM. Now, all of these parts are upgradeable but it would beat having to choose a budget option.

As it stands, the graphics card might struggle to run complex tasks in Blender or any other 3D software. The RAM is also less than what we’d like it to be. How much RAM you need for 3D rendering and modeling is definitely a huge factor, and 8GB is not enough.

The graphics processing unit isn’t impressive either with 2GB, but if you just want to get a prebuilt PC and upgrade slowly by slowly, this might be a decent pick. But you’re probably just better off with the SkyTech Blaze while you’re at it. But before you do decide to buy this prebuilt PC, be sure to check out our other options.

What Are The Best Parts For Building Your Own PC For Blender?

If you don’t like the prebuilt PCs listed above, you can always go for a custom build. And in this section, we’ll go over what you need for that perfect PC build.

CPU Recommendations

The CPU or central processing unit is one of the two biggest focal points for you when it comes to building your PC. The bulk, if not half, of the rendering time, is dictated by just how powerful the CPU is.

You don’t need the most advanced processor there is, but you will need adequate processing power. A 10th-generation Intel Core i5 is sufficient, but we recommend getting the Intel Core i7 of the same generation. If you’re an AMD fanboy, you can go for the Ryzen 5 at the bare minimum.

If you want to spend more money, get the best one there is right now, which is the Intel Core i9 processor or righteously known as the Golden Waffle. The AMD Ryzen 9 5900X is the counterpart.

GPU Recommendations

To guarantee the best performance possible for a Blender PC, you’ll need a graphics card that’s just as powerful as the CPU.

Unlike CPUs, there are several options to choose from, and each one of them as good as the next one. But the biggest factor that will determine what kind of graphics card you’ll be using relies on your budget.

Nvidia GPUs and AMD GPUs have returned to normal pricing and availability after a tumultuous two years. If you’re thinking about going for a professional-grade graphics card, you’ll want to go for the Nvidia GeForce RTX 3000-series or the 4000-series if available.

You’ll want a good GPU such as an Nvidia RTX 3060 if you want to enable GPU acceleration on your system. Having this GPU and combined with the Intel Core i9 will give you a futureproof and powerful PC.

RAM Recommendations

We’re not going to be particular about the brands here, but more focused on the memory capacity. At the bare minimum, you want at least 16GB DDR4 RAM for your workstation. 32GB is ideal, but 64GB might be overkill.

If you do want recommendations for brands, you’ll want to go for something made by Corsair or Kingston.

The Wrap Up

If you’re thinking about getting a good laptop for Blender, you’ll need something just as powerful as the rest of the gaming desktops on here. Larger laptops are also going to be your main target, mostly because you’ll want bigger batteries, strong CPU, a powerful GPU, and at least a 15-inch or 17-inch HD display. Budget gaming PCs are possible options so as long as they meet minimum requirements for Blender.

A 3D modeling computer might be the most decked out computer rig you’ll ever build, and for a good reason.

Working with 3D modeling and rendering takes up a lot of CPU and GPU power. And to speed things up, you’ll need the top of the line processor with enough CPU cores for CPU rendering, and a graphics card to help supplement CPU and GPU rendering.

In this article, we’re going to help you build the best PC possible for 3D modeling and rendering, as well as cover some important topics that will help you make the best decision possible.

But first, we need to understand first two things: 3D modeling and 3D rendering.

What Is 3D Modeling?

3D modeling can be defined as is: it’s the creation of 3D models used for different purposes such as animation and design. With the introduction of 3D printers in the market, 3D modeling has become more widespread than ever. People who’re in the business of 3D printing need to work with 3D software to design and prep whatever it is they need to print.

What Is 3D Rendering?

Rendering is the visualization of a 3D game or object or scene using a rendering software. When you’re creating a 3D model or animation, you’re working with the raw file which is not accessible to anyone. Rendering will finalize whatever it is that you’re working on and produce output that’s made available to the public through a variety of file formats.

For both 3D modeling and rendering, the need for a high powered workstation computer is high. Rendering needs a lot of processing power to carry out the necessary mathematical computations required.

Sample PC Builds for 3D Modeling and Rendering

Some caveats here: the budgets listed may be higher or lower than intended, depending on where you are located and the availability of certain parts.

The builds listed here should also be taken with a grain of salt. They’re designed to give you a lot of rendering power for programs such as Blender, Maya, and Modo to name a few.

Lastly, keep in mind that the best computer might depend on the specs, but ultimately, it will boil down to helping you meet your needs the most. The best computer doesn’t necessarily have to be expensive, but it also doesn’t mean you can skimp out on the graphics cards or processors. Remember, a 3d modeling and rendering PC should be considered an investment.

With that being said, let’s go over some sample builds.

$700: A Cost-Effective Build

• CPU: AMD R5 5600G
• Graphics Card: Zotac Gaming GeForce 1650
• Motherboard: ASRock B550M-HDV
• RAM: G.Skill Trident Z RGB Series 16GB (2 x 8GB)
• Storage: 500GB Western Digital SSD
• Power Supply: EVGA 450 W3

The first build that we have makes use of AMD’s budget CPUs and one of the more decent Nvidia GPUs, the GeForce 1650. Combined with 16GB of RAM and a 512GB SSD, you’re looking at a competent rig with enough 3d modeling and rendering power.

$1200: A Balanced Build

• CPU: AMD Ryzen™ 5 7600X
• Graphics Card: EVGA GeForce GTX 1660 SC Ultra Gaming
• Motherboard: MSI PRO X670-P WiFi ProSeries
• RAM: G.Skill Trident Z5 RGB Series
• Storage 1: Western Digital 500GB WD Blue
• Storage 2: Seagate BarraCuda 2TB Internal Hard Drive
• Power Supply: Cooler Master MWE Gold 650 V2 Full Modular
• CPU Cooler: Noctua NH-U12S SE-AM4

Spending a few more hundred dollars from the cost-effective build above would probably yield you a build something like this.

You’re getting a 6-core CPU, one of the more powerful midrange Nvidia GPUs, enough RAM and storage, and futureproof.

If you noticed, you’re getting 2 sets of storage devices: one SSD and one HDD. The SSD will house your OS, software, and other applications. Your HDD will store all your raw files and rendering output.

Unlike the first build, you’re getting a CPU cooler to help keep the Ryzen 7 processor cool while rendering. The computer graphics power is also sufficient for most GPU render engines.

$1700 – High Performance Build

• CPU: Intel Core i5-13600K
• Graphics Card: GIGABYTE GeForce RTX 3060 Ti
• Motherboard: Gigabyte Z790 UD
• RAM: G.Skill Trident Z5 RGB Series (Intel XMP) 32GB (2 x 16GB)
• Storage 1: SAMSUNG (MZ-V7E500BW) 970 EVO SSD 500GB
• Storage 2: Toshiba X300 4TB Performance & Gaming 3.5-Inch Internal Hard Drive
• Power Supply: Seasonic Focus SSR-850FM, 850W 80+ Gold
• CPU Cooler: be quiet! Dark Rock 4

This would probably be considered the best workstation computer because you’re getting an excellent processor with superior clock speed and one of the best graphics cards on the market right now.

With this build, you’re getting a high-performing PC capable of running most of the popular graphics software and 3D modeling software computer programs thanks to the Intel i5 CPU and the 3060Ti graphics card, complemented by 32GB of RAM and enough SSD storage to host any computer program.

$2900+: Professional Setup

• CPU: Intel i9-13900K
• Graphics Card: ZOTAC Gaming GeForce RTX™ 3080 Ti
• Motherboard: MSI PRO Z790-P WiFi ProSeries Motherboard
• RAM: G.Skill Trident Z5 RGB Series (Intel XMP) 32GB (2 x 16GB)
• Storage 1: SAMSUNG 970 EVO Plus SSD 1TB NVMe M.2
• Storage 2: 2x Toshiba X300 4TB Performance & Gaming 3.5-Inch Internal Hard Drive
• Power Supply: Corsair HX850
• CPU Cooler: NZXT Kraken Z73

At this point, money is no longer an issue for you. You want the best graphics card, the best processor, and the best of everything to give you the best computer possible.

You’re getting an i9 processor combined with an RTX 3080Ti graphics card, though you could also upgrade to a 3090Ti too. Speed is everything in this build, from the insane clock speeds to the incredible read/write speeds from your SSD.

As for futureproofing, this beast will last you for at least five years. There’s nothing in the market that could ever be a mile above either the RTX 3080Ti or the Intel i9-13900K.

PC Building Guide – How To Choose Your Computer Components?

The builds above are just templates, so you don’t necessarily have to follow them to the T. Remember, the best PC for you is the one that’s capable of meeting your needs without forcing you to spend too much money.

For the builds listed above, we’ve stuck to the budget specified but you could always mix and match depending on your needs.

How Do You Choose A CPU?

If this article was made a decade ago, we’d have put more thought into choosing a CPU more so than any other component. And the reason being is that the CPU was involved the most in the rendering process.

Now, GPU rendering overtake CPU rendering, but not by a lot. CPU is still as important as ever in the rendering process, but you get better rendering speeds with a GPU in tow. Now you’ll also use the CPU for other things like gaming and productivity-based computer programs so it doesn’t hurt to invest in something that’s futureproof.

A good start would be AMD’s budget processors or something as powerful as an Intel Core i5 processor if you want some computing power without blowing your entire budget.

How Do You Choose Your Graphics Card?

Unlike graphics design, rendering relies on the strength of your graphics card as it determines how fast it will take to complete the process. GPU rendering, so long as it’s available, is ten times faster than CPU rendering.

With power and strength in mind, you won’t want to work with an integrated GPU. A good and solid choice would be one of the Nvidia graphics cards, preferably RTX. But Nvidia GeForce GTX isn’t a bad choice either, so as long as you’re going for a GTX 1660.

But why are we promoting Nvidia GPUs? Why isn’t AMD GPUs being considered?

Between AMD and NVIDIA’s GPU rendering, Nvidia’s CUDA has better rendering performance than AMD-backed OpenCL. OpenCL is available for other graphics, but CUDA is only for Nvidia.

If your rendering engine can support CUDA, you might as well grab an Nvidia graphics card. If the app is split between CUDA and OpenCL, Nvidia is still the ideal pick. Hopefully, OpenCL has wider support, allowing for better performance.

How Do You Choose RAM?

RAM and the rest of the components aren’t going to be your main concerns, as they’ll only minimally affect any active working process.

For the lower-end builds on here, you’ll notice that we’re sticking with 16GB DDR4 RAM while the midrange and high-end builds have 32GB DDR5. Dual-channel RAM kits are affordable and compatible with the latest motherboards. But if you want exceptional performance, you’ll need to shell out more money to get quad-channel RAMs. You’re looking at spending a few hundred dollars for these quad-channel RAMs, but they are the best hardware components for the RAM category. A single RAM kit may not be sufficient for 3d complex modeling.

The rule of thumb is this: you’ll need at least 8GB of RAM if you want to build a computer for 3D modeling and rendering but you’ll want to shoot for 16GB. More RAM doesn’t necessarily hurt and it will help you speed up things.

How Do You Choose Storage?

A computer for 3D modeling doesn’t need as much storage as a computer for video editing or gaming. Modeling files, images, assets, and raw data have smaller file sizes than expected. But it doesn’t mean that you should be stingy about choosing which storage component to use.

But for the purpose of this article, you’ll need to consider using two different devices, each with their own purpose for storage space.

SSDs or Solid State Drives

Your own computer should have an SSD because while it may not affect rendering performance, it does affect how programs and OS load. SSD read and write times are 100x faster than traditional HDD.

At least 500GB of SSD is more than enough for 3d modeling, graphic design, gaming, and more. If you can shell out a few more hundred dollars for storage, get 1TB SSD. As much as possible, you want to store every program on the SSD so they load faster. You can literally do multiple tasks with ease on an SSD.

HDDs or Hard Disk Drive

Unless you’re getting a 2TB SSD, it makes sense to have a traditional HDD to store your files. And HDDs are relatively cheaper than SSDs.You can easily secure 4TB and it’d still be cheaper than paying for a 1TB SSD.

How Do You Choose Power Supply Units?

Power consumption is something that you’ll need to consider for PC building. A budget PSU may not be ideal since your processor and GPU will have more cores and have high clock speed, so their power consumption is high.

Your rendering workstation should work with a high-quality PSU so you don’t get gimped on power limits while ensuring that you’re protecting all the other computer parts.

FAQs about Rendering Process

We’ve talked about the different builds and the process of selecting computer hardware for the PC build.

For this section, we’ll go over some of the major questions on the render process itself and why rendering images need a lot of hardware power.

Why Does Rendering Take Long?

The rendering speed depends on software and hardware, and the options you have in place. Let’s take a look at a sample scene to illustrate why rendering might take long.

Imagine a simple scene, like panning from left to right on a flower. Not a lot of details to work with here. You’ll have some gradients and lighting involved, different polygon angles, and other complex modeling involved.

Your own PC is trying to compute and repeatedly estimate different things at once, ranging from the changing of the color gradients to light bouncing off of reflective surfaces, creating shadows, and so on. Depending on how detailed the flower is, each petal might house hundreds if not thousands of polygons at one time.

To keep it simple, the PC carries out complex mathematical equations on the fly to simulate what the human eye is seeing. A high clocked CPU and a GPU with enough video memory can make short work of rendering compred to another rendering workstation that’s a bit underpowered than the former.

Do You Need a Powerful CPU or GPU?

For the previous section, we were talking about rendering a flower panned from left to right. But what if we’re rendering something complicated, like visual effects or a detailed 3d model of a human being, then you’ll definitely need a powerful CPU.

Processing data at this level will take up a lot of video memory and will work more cores than rendering a flower scene. This will vary amongst different GPU render engines, or any render engine for that matter. What matters here is that you get the CPU with the highest clock speed and as many cores possible that money can buy, sufficient wattage, a decent amount of RAM slots, and GPU with maximum speed.