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DATA SCIENCE, EDITORIAL, MACHINE LEARNING

Best Workstations for Deep Learning, Data Science, and Machine Learning (ML) for 2023

Empower your AI journey with high-performance computing. We’ve examined over 8000 desktops [1] to bring you the best workstations for deep learning, machine learning, and data science, tailored to every budget.

Last updated June 13, 2023

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Building or purchasing an AI PC offers unparalleled adaptability, allowing you the freedom to upgrade components like GPUs as per your unique requirements. Future-proof your workstation by incorporating the latest GPU models, such as the GeForce RTX 4070 Ti, RTX 4080, and RTX 4090. AI PCs are distinguished for their capacity to handle power-intensive tasks thanks to their superior cooling systems and the wide range of CUDA-Enabled GPUs available.

Data is driving a fundamental shift in business operations, leading to an increased demand for skilled data scientists. Workstations powered by top-tier GPUs, like RTX and Quadro RTX, are frontlining this transformation. NVIDIA-powered data science workstations swiftly transform large datasets into actionable insights, thanks to a comprehensive suite of tested and optimized data science software.

GPU-Accelerated Libraries for AI and HPC | Source: NVIDIA [15]

These high-performing workstations have many benefits: maximized productivity for data scientists due to a fully integrated hardware and software stack, quicker model development and training courtesy of the powerful GPUs, and enterprise-class reliability and support for trusted, consistent performance.

The future is here with next-gen workstations equipped with cutting-edge Intel® Xeon® W processors and top-of-the-line smart network interface cards. They offer unprecedented performance, advanced features, and efficiency, ideal for both creative and technical professionals.

Investing in an AI PC or upgrading your current one provides significant advantages, particularly for data-intensive tasks. Armed with the latest GPUs and fully-optimized data science software, these workstations symbolize the future of data processing and handling. Dive into the future today with these transformative workstations.

We continue to receive a large number of emails from AI enthusiasts asking for the best AI rigs. So we made this list of the best PCs for AI projects. Please contact us at pub@towardsai.net if you have any suggestions to add to the list — we’ll be updating this article as we come up with newer and better AI workstations to power your every need.

Disclosure: Our editorial team at Towards AI writes authentic and trustworthy reviews and may receive a small compensation for products we select to support Towards AI’s efforts. For this article, as an Amazon Associate, Towards AI may receive a small commission from qualifying purchases made from it (at no extra cost to the buyer). For feedback, questions, or concerns, please email us at pub@towardsai.net.

📚 Check out our editorial recommendations for the best deep learning laptop. 📚

Let’s get started!

For Budgets under $ 1,000.00 ↓

For a mid-range AI-PC setup, selecting a powerful processor is crucial. Intel’s i3 to i5 processors are robust options, especially from the 10x to 11x F or K series, such as the Intel Core i5–10400F. While these processors lack an integrated GPU, they can handle most AI tasks adeptly. Don’t overlook AMD CPUs in your considerations either; they’ve earned praise for delivering similar performance to Intel CPUs at a more budget-friendly price, making them a compelling alternative for cost-conscious AI-PC builders.

Source: Amazon

Empowered PC Stratos

Great PC under $ 1k. Ideal for data leaders who care about Intel processors, suitable RAM size, fair expandability, and RTX GPUs under a $ 1k budget.

Specs:

• Processor: Intel Core i5–10400F Six Core Processor (12MB Cache, 2.9GHz-4.3GHz) 65W
• Memory: 16 GB SDRAM
• Hard Drives: 512 GB NVMe SSD
• GPU: NVIDIA GeForce RTX 3060 Ti 8GB
• Computing Power: 8.6 [9]
• OS: Windows 11 Home 64 bit
• Features: Wi-Fi, Bluetooth, ARGB High Airflow Fans
• Accessories: Wired LED Backlit USB Gaming Keyboard and Mouse Included, 3-Year CUK Limited Warranty
• Power supply: 500W Gold PSU

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Source: Amazon

MINISFORUM NUCX

Best PC under $ 1k. Ideal for data leaders who care about Intel processors, suitable RAM size, fair expandability, and RTX GPUs under a $ 1k budget.

Specs:

• Processor: Intel I7 11800H 2.3GHz base, 4.6GHz max turbo frequency
• Memory: 32 GB DDR4
• Hard Drives: 512 GB NVMe SSD
• GPU: NVIDIA GeForce RTX 3070
• Computing Power: 8.6 [9]
• OS: Windows 11 Pro
• Features: Wi-Fi, Bluetooth
• Ports: Thunderbolt 4 (8K@60Hz), HDMI (4k@60Hz), RJ45 2.5G, 3x USB 3.2 Type-A, SD Card Slot x1, 3.5mm combo Jack x1

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For Budgets ~$ 1500

If you can stretch your budget a bit, we strongly recommend pursuing an RTX 30x PC and future-proof your rig even more. Such as this Amazon bestseller:

Source: Amazon

Empowered PC ROG Strig Ak

Best PC approximating $ 1.5k. Ideal for leaders who care about AMD processors, suitable RAM size, RTX 30x GPUs, and considerable expandability.

Specs:

• Processor: Intel Core i7–11700F
• Memory: 64 GB DDR4 SDRAM
• Hard Drives: 1 TB NVMe SSD + 2 TB HDD
• GPU: NVIDIA GeForce RTX 4 070 (8 GB GDDR6)
• Computing Power: 8.6 [9]
• Ports: 5 USB 3.2 Gen 1 Type-Ax 2, 1 USB 3.2 Gen 2 Type-C, USB 2.0 Type A, Audio line-out x3, HDMI, Ethernet (RJ-45), DisplayPort x3
• OS: Windows 11 Pro
• Connectivity: Wi-Fi: 6+, Bluetooth

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For Budgets ~$ 2000.00

MSI Aegis RS

Tie-Best PC approximating $ 2k. Ideal for data leaders who care about Intel processors, suitable RAM size, RTX 40x GPUs, and considerable expandability.

Specs:

• Processor: Intel Core i7 13700KF
• Memory: 64GB DDR4
• Hard Drives: 2 TB NVMe SSD
• GPU: NVIDIA GeForce RTX 4070 12GB GDDR6
• Computing Power: 8.9 [9]
• Ports: 1x USB Type-C, 5x USB 3.2 Gen 2 Type-A, 1x Thunderbolt 4/USB4 40Gbps, 1x HDMI, 1x DisplayPort, 1x RJ-45 Ethernet
• OS: Windows 11 Home
• Connectivity: Wi-Fi 6, Bluetooth

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For Budgets ~$ 3k

Source: Amazon

Velztorm Praetix CTO

Best PC ~$ 3k. Beautiful AI rig, this AI PC is ideal for AI leaders who want the best in processors, large RAM, expandability, an RTX 4080 GPU, and a large power supply.

Specs:

• Processor: Intel Core i9 13900KF 3.00GHz up to 5.8GHz
• Memory: 64GB DDR5
• Hard Drives: 1 TB NVMe SSD + 2 TB HDD
• GPU: NVIDIA GeForce RTX 4080 16GB
• Computing Power: 8.9 [9]
• Ports: 4x USB 2.0, 1 HDMI, 1 DisplayPort, 2 USB 3.2 Type-C Gen2
• OS: Windows 11 Pro
• Connectivity: 802.11 a/b/n/ac/ax WiFi, Bluetooth 5.2, Ethernet LAN RJ 45
• Power supply: 1000w

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Monster AI Rigs — Unlimited Budgets!

Source: Amazon

CUK Continuum

[Tie] Best AI workstation. Beautiful AI rig, this AI PC is ideal for data leaders who want the best of the best but are inclined toward an AMD processor.

Specs:

• Processor: AMD 9 5950X 3.4GHz up to 4.9GHz
• Memory: 64 GB DDR4.
• Hard Drives: 1 TB NVMe SSD + 3 TB HDD.
• GPU: NVIDIA GeForce RTX 3090 24GB.
• Computing Power: 7.5 [9]
• Ports: 1x HDMI 2.0, 1x USB 3.1 Type-C, 2x USB 3.1, 1x USB 2.0.
• OS: Windows 11 Home.
• Connectivity: WiFi 802.11ax, Gigabit LAN (Ethernet), Bluetooth.
• Power supply: 750w

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Source: Amazon

CUK Mantis

[Tie] Best AI workstation. Beautiful AI rig, this AI PC is ideal for data leaders who want the best of the best but are inclined toward an Intel processor and a very large power supply. This AI workstation is the top of the line of our $ ~2k recommendation.

Specs:

• Processor: AMD 9 5950X 3.4GHz up to 4.9GHz
• Memory: 64 GB DDR4.
• Hard Drives: 1 TB NVMe SSD + 2 TB HDD.
• GPU: NVIDIA GeForce RTX 3090 24GB.
• Computing Power: 7.5 [9]
• Ports: 1x HDMI 2.0, 1x USB 3.1 Type-C, 2x USB 3.1, 1x USB 2.0.
• OS: Windows 11 Home.
• Connectivity: WiFi 802.11ax, Gigabit LAN (Ethernet), Bluetooth.
• Power supply: 850w

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Conclusion

We hope you find this list helpful in searching for an AI workstation for deep learning, machine learning, and data science projects. If you come across any phenomenal AI workstations, such as those mentioned in this list, please let us know by emailing us. If, instead of buying an AI desktop, you’d like to build one, stay tuned. We’ll be releasing a new list of recommendations with the best components to buy for your AI-powered workstation.

We’d also love to show our readers how to build an AI rig end-to-end. So if you represent a supplier and would like to sponsor an upcoming tutorial showing our audience how to build an AI rig, please feel free to contact us.

Thank you for reading!

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References

[1] RTX Performance AI Rigs, Amazon, https://www.amazon.com/s?k=rtx+64gb+desktop&ref=nb_sb_noss_2

[2] Intel 10750H Q2 2020, Intel, https://www.intel.com/content/www/us/en/products/processors/core/i7-processors/i7-10750h.html

[3] Intel 9750H, Intel, https://www.intel.com/content/www/us/en/products/processors/core/i7-processors/i7-9750h.html

[4] AMD Ryzen 7 7800H, AMD, https://www.amd.com/en/products/apu/amd-ryzen-7-4800h

[5] Intel 10980 HK, Intel, https://ark.intel.com/content/www/us/en/ark/products/201838/intel-core-i9-10980hk-processor-16m-cache-up-to-5-30-ghz.html

[6] Intel 10875 HK. Intel, https://ark.intel.com/content/www/us/en/ark/products/202329/intel-core-i7-10875h-processor-16m-cache-up-to-5-10-ghz.html

[7] RTX 2080 vs. AMD Radeon Pro 5500M, User Benchmark, https://gpu.userbenchmark.com/Compare/Nvidia-RTX-2080-vs-AMD-Radeon-Pro-5500M/4026vsm960765

[8] RTX Performance Desktops, Amazon, https://www.amazon.com/s?k=rtx+64gb+desktop&ref=nb_sb_noss_2

[9] NVidia CUDA Geforce GPUS, Nvidia, https://www.nvidia.com/en-us/geforce/gaming-laptops/

[10] Nvidia CUDA Quadro GPUS, Nvidia, https://www.nvidia.com/object/quadro-for-mobile-workstations.html

[11] GPU UserBenchmark, https://gpu.userbenchmark.com/Compare/Nvidia-RTX-3060-vs-Nvidia-RTX-2070S-Super-Mobile-Max-Q/4105vsm1168355

[12] GPU UserBenchmark, https://gpu.userbenchmark.com/Compare/Nvidia-RTX-3080-Laptop-vs-Nvidia-RTX-2080S-Super-Mobile-Max-Q/m1443565vsm1114823

[13] CUDA-Enabled GeForce and TITAN Products, https://developer.nvidia.com/cuda-gpus

[14] Max-Q Design, Nvidia, https://www.nvidia.com/en-us/geforce/gaming-laptops/max-q/

[15] NVIDIA CUDA-X

GPU-Accelerated Libraries for AI and HPC, https://www.nvidia.com/en-us/technologies/cuda-x/