Weigh NVIDIA A16, A40, A100, and L40S by cores, memory, and TFLOPS to pick a Vultr Cloud GPU variant.
Vultr Cloud GPU offers multiple GPU options for different workloads. You can use these GPUs for tasks such as machine learning, artificial intelligence (AI), 3D rendering, and complex simulations.
Vultr Cloud GPU offers the following GPU families: AMD Instinct™ MI355X, NVIDIA HGX B200, AMD Instinct™ MI325X, AMD Instinct™ MI300X, NVIDIA GH200, NVIDIA HGX H100, NVIDIA L40S, NVIDIA HGX A100, NVIDIA A100 PCIe, NVIDIA A40, and NVIDIA A16. The following sections describe the core differences between the GPU variants to help you choose an option for a specific workload.
This section provides technical and performance data to compare the NVIDIA A16, A40, A100, and L40S GPUs based on their Compute Unified Device Architecture (CUDA) cores, trillion floating-point operations per second (TFLOPS), and parallel processing.
The following table compares the performance of the Cloud GPUs that Vultr offers:
vGPU: A virtualization technology that shares a physical GPU among multiple virtual machines (VMs) to run graphics and compute workloads in a virtualized environment. vGPU suits tasks such as virtual desktop infrastructure (VDI), graphics-intensive applications, and AI workloads in shared setups.
Passthrough: A virtualization technique that assigns a physical GPU directly to a single VM and gives the VM exclusive access to the GPU's resources. Unlike vGPU, which shares a GPU among multiple VMs, passthrough dedicates the entire GPU to one VM for maximum performance and compatibility.
CUDA Cores: Processing units designed to work with NVIDIA's CUDA programming model. CUDA cores perform parallel processing and accelerate computing tasks focused on graphics rendering. They often use a Single Instruction, Multiple Data (SIMD) architecture, which executes a single instruction simultaneously on multiple data elements and results in high throughput for parallel computing.
Tensor Cores: Hardware components in NVIDIA GPUs that accelerate matrix-based computations common in deep learning and AI workloads. Tensor Cores speed up the mathematical operations in neural network training and inference through mixed-precision computing, which performs certain parts of a calculation in higher precision and the rest in half precision while maintaining accuracy through error correction and accumulation.
Matrix Cores: Hardware units in AMD Instinct™ GPUs that accelerate matrix-based computations central to AI and high-performance computing (HPC). Matrix Cores use mixed-precision arithmetic with data types such as FP16, BF16, and INT8 to accelerate operations such as matrix multiplications.
AMD Instinct™ MI355X: Vultr Cloud GPU, powered by the AMD Instinct™ MI355X, is built for AI, deep learning, and HPC workloads. The MI355X uses the CDNA 4 architecture and offers 288 GB of High Bandwidth Memory 3e (HBM3e) per GPU, with FP8 and FP4 compute for training and inference of very large models. Its design emphasizes memory bandwidth and compute efficiency for generative AI, large language models (LLMs), and large-scale scientific simulations. Learn more about Vultr Cloud GPU AMD Instinct™ MI355X.
NVIDIA HGX B200: Vultr Cloud GPU, powered by the NVIDIA HGX B200, uses the NVIDIA Blackwell architecture for AI acceleration. The B200 is designed for large-scale AI workloads, including generative AI, LLM training, and scientific computing, and supports FP8 and FP4 precision. It offers up to 192 GB of HBM3e memory per GPU and high memory bandwidth for training and deploying large models. Its NVLink-based architecture supports multi-GPU scaling for enterprise AI workloads. Use cases include research, AI inference at scale, and data-intensive computing. Learn more about Vultr Cloud GPU NVIDIA HGX B200.
AMD Instinct™ MI325X: Vultr Cloud GPU, powered by the AMD Instinct™ MI325X, is designed for AI training, inference, and HPC workloads that require large GPU memory capacity.
AMD Instinct™ MI300X: Vultr Cloud GPU, powered by the AMD Instinct™ MI300X, is designed for AI and HPC applications. With high memory bandwidth and support for large-scale models, the MI300X runs training and inference for AI and deep learning tasks. Use it for scalable data processing and scientific simulations. Learn more about Vultr Cloud GPU AMD Instinct™ MI300X.
NVIDIA GH200 Superchip: Vultr Cloud GPU, powered by the NVIDIA GH200 Superchip, combines multiple GPU components for AI and HPC workloads. This design improves scalability and efficiency for complex tasks that demand substantial computing power. Use cases include large-scale AI deployments, scientific simulations, and data analytics. Learn more about Vultr Cloud GPU GH200 Superchip.
NVIDIA HGX H100: Vultr Cloud GPU, powered by the NVIDIA HGX H100, is designed for AI workloads, including LLM training and inference. Its architecture and Tensor Cores deliver higher performance and efficiency for compute-intensive applications. Use it for research and complex tasks that require significant computational resources. Learn more about Vultr Cloud GPU H100.
NVIDIA L40S: Vultr Cloud GPU, powered by the NVIDIA L40S, is designed for graphics, AI inference, and real-time processing. The L40S handles tasks such as 3D visualization, virtual environments, and video processing for creative industries and high-end computing projects. You can use the L40S to deliver smoother graphics and faster data processing while keeping infrastructure scalable and cost-effective. Learn more about Vultr Cloud GPU L40S.
NVIDIA HGX A100: Vultr Cloud GPU, powered by the NVIDIA A100 Tensor Core GPU in SXM format, is designed for AI and data science workloads. The SXM format allows for better power delivery and thermal management, which improves performance. Use it to train large neural networks and run extensive computational tasks. Learn more about Vultr Cloud GPU A100.
NVIDIA A100 PCIe: Vultr Cloud GPU, powered by the NVIDIA A100 Tensor Core GPU in PCIe format, is suitable for tasks such as AI training and deep learning. This version connects through the PCIe interface, which makes it compatible with many server setups. With its processing capabilities and high memory bandwidth, it helps you manage large datasets and complex models on scalable infrastructure. Learn more about Vultr Cloud GPU A100.
NVIDIA A40: Vultr Cloud GPU, powered by the NVIDIA A40, is designed for workloads that require advanced visualization, such as 3D rendering, virtual production, and complex simulations. This GPU offers high memory capacity and processing power for data-intensive tasks. You can use the A40 to manage large datasets, perform real-time rendering, and support creative and scientific workflows. Learn more about Vultr Cloud GPU A40.
NVIDIA A16: Vultr Cloud GPU, powered by the NVIDIA A16, supports low-latency VDI, transcoding, and AI inference workloads. Learn more about Vultr Cloud GPU A16.
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