NVIDIA GPUs with 12 GB of video memory
If your goal is to build a Deep Learning workstation on a tight budget, you may consider NVIDIA GPUs with 12 GB of memory which allow you to run some experiments with generative AI. In addition, if you aim to learn a Deep Learning framework such as PyTorch or Tensorflow even less video memory is enough. It is possible to move your experiments into the cloud to a GPU with more memory or even several GPUs after you developed and debugged your code locally.
As always, older models can offer lower prices at the expense of computation performance as newer models have more CUDA cores. Also, newer GPUs offer additional acceleration of training and inference workloads. NVIDIA GPUs with Volta architecture released in 2017 added Tensor Cores that speed up matrix operations widely used in AI and deep learning. NVIDIA architectures following Volta added improvements to tensor cores. Finally, one should not discount improvements in video RAM which increase memory bandwidth from generation to generation.
GeForce GTX TITAN X
Released in 2015, this GPU is powered by NVIDIA’s Maxwell architecture, designed for solid performance across various applications. It comes equipped with GDDR5 memory and provides a 336.5 GB/s memory bandwidth for efficient data processing. With a 384-bit memory interface, it ensures smooth data handling and performance.
Featuring 3072 CUDA cores, this GPU is built for parallel computing tasks, making it suitable for gaming, rendering, and general computing. While it doesn’t have Tensor Cores, it’s optimized for FP32 precision, ideal for tasks requiring single-precision floating-point calculations.
The PCI Express 3.0 interface offers broad compatibility, and its active cooling system keeps the GPU running cool even under heavy use. With a 250W power requirement, it’s ready to deliver reliable performance as long as your system can support its power needs.
Quadro M6000
Built on NVIDIA’s Maxwell architecture and launched in 2015, this GPU is designed for reliable performance across a range of applications. It features GDDR5 memory with a 317 GB/s memory bandwidth and a 384-bit memory interface, enabling efficient data transfer and smooth operation under load.
With 3072 CUDA cores, this GPU excels at parallel processing, making it ideal for tasks like content creation, rendering, and computational workloads. While it doesn’t include Tensor Cores, it supports FP32 precision, perfect for single-precision tasks.
The PCI Express 3.0 x16 interface ensures compatibility with most systems, and the active cooling system helps keep temperatures in check during intensive use. With a 250W power requirement, it provides dependable performance with adequate system support.
For those who need more memory, a variant of the M6000 model is available with 24 GB of memory, offering enhanced capacity for demanding applications.
Tesla M40
Released in 2015 and powered by NVIDIA’s Maxwell architecture, this GPU is crafted for efficient and reliable performance. It features GDDR5 memory with a 288 GB/s memory bandwidth and a 384-bit memory interface, ensuring smooth data flow for a variety of tasks.
Equipped with 3072 CUDA cores, this GPU is well-suited for parallel processing, making it ideal for inference workloads, and computational tasks. While it lacks Tensor Cores, it supports FP32 precision, delivering solid performance for single-precision tasks.
The PCI-Express 3.0 x16 interface ensures broad compatibility, and its passive cooling system allows for silent operation, though it requires 250W of power to keep up with demanding applications.
For users needing additional memory, a variant of the M40 model is available with 24 GB of memory, providing extra capacity for memory-intensive workloads.
Tesla P100 PCIe 12 GB
Released in 2016 and powered by NVIDIA’s Pascal architecture, this GPU is built for high-performance computing. It comes with HBM2 memory and offers a substantial 549 GB/s memory bandwidth through a 3072-bit memory interface, allowing for rapid and efficient data handling.
With 3584 CUDA cores, this GPU is optimized for parallel processing, making it ideal for tasks in scientific computing, rendering, and other demanding applications. Although it doesn’t feature Tensor Cores, it supports both FP16 and FP32 precision, making it well-suited for applications requiring single and half-precision calculations.
Equipped with a PCI-Express 3.0 x16 interface for compatibility and a passive cooling system for quiet operation, this GPU maintains efficiency with a 250W power requirement.
For users needing more memory, a variant of the P100 model is available with 16 GB of memory, offering expanded capacity for memory-intensive workloads.
TITAN X Pascal
Launched in 2016 and powered by NVIDIA’s Pascal architecture, this GPU is designed to deliver high performance across various demanding tasks. It features GDDR5X memory with an impressive 480.4 GB/s memory bandwidth and a 384-bit memory interface, ensuring fast and efficient data processing.
With 3584 CUDA cores, this GPU excels at parallel processing, making it ideal for tasks such as gaming, rendering, and scientific computing. Although it doesn’t have Tensor Cores, it supports both FP16 and FP32 precision, providing strong performance for single- and half-precision workloads.
The PCI-Express 3.0 x16 interface ensures smooth compatibility, while the active cooling system keeps the GPU operating efficiently under heavy loads. Requiring 250W of power, it’s engineered to provide consistent, reliable performance.
TITAN Xp
Released in 2017 and built on NVIDIA’s Pascal architecture, this GPU is crafted for powerful performance across a range of applications. It’s equipped with GDDR5X memory, delivering a substantial 547.7 GB/s memory bandwidth through a 384-bit memory interface, ensuring rapid data processing for demanding workloads.
With 3840 CUDA cores, this GPU is ideal for tasks requiring high parallel processing capabilities, such as gaming, rendering, and scientific computations. Although it lacks Tensor Cores, it supports FP16 and FP32 precision, making it a reliable choice for both single- and half-precision calculations.
The PCI-Express 3.0 x16 interface ensures system compatibility, and the active cooling system maintains optimal temperatures even during intensive use. With a power requirement of 250W, this GPU combines efficiency and consistent performance for professional and enthusiast applications.
TITAN V
Introduced in 2017 and powered by NVIDIA’s Volta architecture, this GPU is engineered for high-performance computing and AI tasks. It features HBM2 memory with an impressive 651.3 GB/s memory bandwidth and a 3072-bit memory interface, enabling fast and efficient data transfer for even the most demanding applications.
With 5120 CUDA cores and 640 Tensor Cores, this GPU excels in parallel processing and AI acceleration, making it ideal for deep learning, scientific research, and complex computations. The Tensor Cores are optimized for FP16 precision, while the GPU itself supports INT32 and FP32 data types, providing flexibility for a range of precision requirements.
The PCI-Express 3.0 x16 interface ensures compatibility with a wide range of systems, and its active cooling system keeps the GPU operating at peak performance under heavy loads. Drawing 250W of power, this Volta-based GPU delivers robust performance for advanced computing tasks.
GeForce RTX 2060 12 GB
Launched in 2021 and powered by NVIDIA’s Turing architecture, this GPU is crafted for versatile, high-performance computing. Equipped with GDDR6 memory and offering 336 GB/s memory bandwidth through a 192-bit memory interface, it’s built to handle data-intensive tasks with ease.
With 2176 CUDA cores and 272 second-generation Tensor Cores, this GPU excels in parallel processing and AI workloads, making it suitable for deep learning, inference, and more. The Tensor Cores are optimized for precision tasks, supporting INT1, INT4, INT8 for inference as well as FP16 for more complex operations, while the GPU also supports FP32 data types.
The PCI-Express 3.0 x16 interface ensures broad compatibility, and the active cooling system maintains optimal performance even during heavy use. With a 184W power requirement, this Turing-based GPU offers a balance of power and efficiency for advanced applications.
GeForce RTX 3060 12 GB
Released in 2021 and powered by NVIDIA’s Ampere architecture, this GPU is designed for high-performance computing across a range of tasks. It features GDDR6 memory with a 360 GB/s memory bandwidth and a 192-bit memory interface, allowing for efficient data transfer and smooth operation.
Equipped with 4584 CUDA cores and 112 third-generation Tensor Cores, this GPU excels in both parallel processing and AI acceleration, making it ideal for advanced workloads. The Tensor Cores support a wide array of data types, including INT1, INT4, INT8, BF16, FP16, and TF32, while the GPU itself handles INT32 and FP32 precision, providing flexibility for various computing needs.
The PCI Express Gen 4 interface ensures high-speed communication with your system, and the active cooling system keeps temperatures in check under heavy loads. With a 170W power requirement, this Ampere-based GPU strikes a balance between power and efficiency for modern applications.
GeForce RTX 3080 Ti
Launched in 2021 and built on NVIDIA’s powerful Ampere architecture, this GPU is engineered for top-tier performance. Featuring GDDR6X memory with an impressive 912.4 GB/s memory bandwidth and a 384-bit memory interface, it’s designed for smooth, high-speed data processing, even under demanding conditions.
With 10,240 CUDA cores and 320 third-generation Tensor Cores, this GPU excels in parallel computing and AI acceleration, making it ideal for complex applications like deep learning and scientific simulations. The Tensor Cores support a range of precision formats, including INT1, INT4, INT8, BF16, FP16, and TF32, while the GPU itself supports INT32 and FP32, providing versatility for various precision needs.
The PCI Express Gen 4 interface ensures high-speed connectivity, and the active cooling system keeps performance steady, even during intensive tasks. With a 350W power requirement, this Ampere-based GPU is built to deliver uncompromising power for advanced computing.
RTX A2000 12 GB
Released in 2021 and powered by NVIDIA’s Ampere architecture, this GPU combines efficiency with impressive performance for a range of applications. It comes with GDDR6 memory, delivering a 288 GB/s memory bandwidth through a 192-bit interface, ensuring quick and smooth data handling.
With 3328 CUDA cores and 104 third-generation Tensor Cores, this GPU is equipped for parallel processing and AI workloads, making it a solid choice for tasks like deep learning and complex computations. The Tensor Cores support multiple precision formats, including INT1, INT4, INT8, BF16, FP16, and TF32, while the GPU also handles INT32 and FP32, offering flexibility across diverse workloads.
The PCI Express Gen 4 interface ensures fast connectivity, and the active cooling system keeps temperatures in check, even with a low 70W power requirement, making this GPU efficient and reliable for energy-conscious setups.
GeForce RTX 3080 12 GB
Unveiled in 2022 and powered by NVIDIA’s Ampere architecture, this GPU is designed for unmatched performance in high-demand environments. It features GDDR6X memory with a blazing 912.4 GB/s memory bandwidth and a 384-bit memory interface, making it ideal for intensive data processing tasks.
With 8960 CUDA cores and 280 third-generation Tensor Cores, this GPU is built for advanced parallel computing and AI acceleration, handling complex tasks like deep learning and scientific simulations with ease. The Tensor Cores support a wide range of precision formats, including INT1, INT4, INT8, BF16, FP16, and TF32, while the GPU itself supports INT32 and FP32, offering flexibility for both high-precision and AI-driven applications.
The PCI Express Gen 4 interface ensures high-speed connectivity with the system, and its active cooling system maintains optimal performance under heavy workloads. Drawing 350W of power, this Ampere-based GPU provides robust power for cutting-edge computing needs.
GeForce RTX 4070 Ti
Released in 2023 and driven by NVIDIA’s Ada Lovelace architecture, this GPU is designed for high-performance tasks across various applications. Equipped with GDDR6X memory and a 504.2 GB/s memory bandwidth over a 192-bit interface, it ensures rapid and efficient data processing.
With 7680 CUDA cores and 240 fourth-generation Tensor Cores, this GPU is optimized for parallel processing and advanced AI workloads, making it ideal for deep learning, scientific computing, and high-resolution rendering. The Tensor Cores support multiple precision formats, including FP8, FP16, BF16, TF32, INT8, and INT4, offering flexibility for a range of computational needs.
The PCI Express Gen 4 interface guarantees fast system connectivity, while the active cooling system maintains stability and performance under intense usage. Requiring 285W of power, this Ada Lovelace-based GPU is a robust and efficient choice for cutting-edge computing environments.
GeForce RTX 4070
Launched in 2023 and powered by NVIDIA’s Ada Lovelace architecture, this GPU is crafted for high-efficiency performance across diverse applications. Featuring GDDR6X memory with a 504.2 GB/s memory bandwidth and a 192-bit interface, it provides swift and smooth data handling for intensive tasks.
With 5888 CUDA cores and 184 fourth-generation Tensor Cores, this GPU is equipped for advanced parallel processing and AI-driven workloads, ideal for the beginners in deep learning. The Tensor Cores offer broad support for precision formats, including FP8, FP16, BF16, TF32, INT8, and INT4, giving it the versatility to tackle various computational needs.
The PCI Express Gen 4 interface ensures rapid system connectivity, while the active cooling system keeps it performing optimally even under heavy load. With a 200W power requirement, this Ada Lovelace-based GPU balances power efficiency and performance for cutting-edge computing environments.
GeForce RTX 4070 SUPER
Released in 2024 and built on NVIDIA’s Ada Lovelace architecture, this GPU is designed for high-performance and efficient processing. Equipped with GDDR6X memory and a 504.2 GB/s memory bandwidth over a 192-bit interface, it offers fast, reliable data handling for complex applications.
With 7168 CUDA cores and 224 fourth-generation Tensor Cores, this GPU is optimized for demanding parallel processing and AI tasks, making it an excellent choice for deep learning, scientific computing, and advanced graphics. The Tensor Cores support a wide range of precision formats, including FP8, FP16, BF16, TF32, INT8, and INT4, allowing for flexibility across various workload types.
The PCI Express Gen 4 interface ensures fast system connectivity, while the active cooling system maintains optimal performance under heavy use. With a 220W power requirement, this Ada Lovelace-based GPU provides a powerful and efficient solution for cutting-edge computing needs.
GeForce RTX 4070 GDDR6
Built on NVIDIA’s Ada Lovelace architecture and released in 2024, this GPU is designed for powerful, efficient performance. It features GDDR6 memory with a 480 GB/s memory bandwidth across a 192-bit interface, enabling fast and smooth data processing for demanding applications.
With 5888 CUDA cores and 184 fourth-generation Tensor Cores, this GPU excels at parallel processing and AI-driven workloads, making it ideal for deep learning, scientific computing, and advanced graphics. The Tensor Cores support multiple precision formats, including FP8, FP16, BF16, TF32, INT8, and INT4, allowing flexibility across a range of applications.
The PCI Express Gen 4 interface provides high-speed connectivity, while the active cooling system ensures stable performance under heavy loads. Drawing 200W of power, this Ada Lovelace-based GPU offers a balance of power and efficiency, perfect for modern computing needs.
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