Comparing Enterprise NVIDIA GPUs: A100, H100, T4, A30, and Jetson - Which One to Pick
- server-parts.eu server-parts.eu
- Sep 7, 2024
- 3 min read
Updated: Oct 7
NVIDIA offers a wide range of GPUs built for enterprise infrastructure, covering AI, data analytics, and high-performance computing (HPC). Each model serves a different workload, from AI training and inference to visualization and edge computing.
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NVIDIA A100 GPU (Ampere, 2020)
Best for: AI Training, Inference, and HPC
Memory: Up to 80 GB HBM2e
Performance:The A100 supports MIG (Multi-Instance GPU), allowing one GPU to be partitioned into multiple isolated instances. It remains a foundation in enterprise AI and HPC deployment.
Use Case:Large model training, scientific computing, data-intensive analytics.
NVIDIA A30 GPU (Ampere, 2021)
Best for: Mixed AI Inference / Training and Analytics
Memory: 24 GB HBM2
Performance:Built for hybrid workloads, the A30 handles inference and training tasks effectively and supports MIG.
Use Case:Organizations needing flexible GPU use across AI and analytics workloads.
NVIDIA A40 GPU (Ampere, 2020)
Best for: Visualization + AI Acceleration
Memory: 48 GB GDDR6
Performance:Optimized for rendering, GPU-accelerated graphics, VDI, and visual workloads, while offering support for AI workloads.
Use Case:Design, architecture, simulation, visualization tasks with AI components.
NVIDIA RTX A6000 GPU (Ampere, 2020)
Best for: High-End Visualization, AI, Simulation
Memory: 48 GB GDDR6
Performance:A professional workstation-class GPU that balances rendering and AI capabilities.
Use Case:Rendering, simulation, design, and AI-augmented visualization in enterprise environments.
NVIDIA H100 GPU (Hopper, 2022)
Best for: Next-Gen AI, LLMs, HPC
Memory: 80 GB HBM3 (94 GB in the NVL configuration)
Performance:Offers significant advances over A100, with Transformer Engines, updated Tensor Cores, and stronger performance for large-scale AI tasks.
Use Case:Training large language models, real-time analytics, high-end scientific workloads.
NVIDIA H200 GPU (Hopper / next iteration, 2024)
Best for: AI & HPC at scale
Memory: ~141 GB HBM3e (per GPU)
Performance:An evolution over H100, the H200 offers increased memory bandwidth and capacity, making it strong for next-generation AI and HPC deployments.
Use Case:Massive AI training clusters, cutting-edge model deployment, exascale computing.
NVIDIA L4 GPU (Ada Lovelace / data center, 2023)
Best for: AI Inference in Cloud & Edge
Memory: 24 GB GDDR6
Performance:Serves as the successor to T4. It is optimized for throughput and power efficiency in inference workloads.
Use Case:Scalable inference, video processing, cloud-native AI services.
NVIDIA L40 / L40S GPU (Ada Lovelace, 2023)
Best for: Visual + AI Workloads
Memory: 48 GB GDDR6
Performance:Replaces A40 in many use cases, combining strong visualization/rendering performance with AI acceleration.
Use Case:Visualization, design, rendering with AI-enabled workflows.
NVIDIA RTX 6000 Ada (Ada Lovelace, 2022)
Best for: Visualization, Simulation, AI Tasks
Memory: 48 GB GDDR6
Performance:A newer workstation GPU that replaces RTX A6000 in many workloads, offering improved efficiency and feature set.
Use Case:Workstations for design, simulation, AI-infused visualization workflows.
NVIDIA B100 / B200 GPUs (Blackwell architecture, 2025)
Best for: Large-Scale AI Training & Inference
Memory: HBM3e (expected capacities up to ~192 GB depending on model)
Performance:These are the upcoming next-generation GPUs succeeding Hopper, intended to push AI training, inference, and HPC further.
Use Case:Future AI/data center deployments, exascale computing, next-tier LLM training.
NVIDIA Jetson Orin / Edge AI Modules (2020)
Best for: Edge AI & Embedded Systems
Memory: Up to 32 GB (LPDDR5 or similar)
Performance:Jetson Orin modules bring updated performance to robotics, industrial edge, and embedded AI systems.
Use Case:Edge inference, robotics, IoT, autonomous systems requiring local AI.
Choosing the Right NVIDIA GPU
For AI Training & HPC: H200, H100, A100, B100/B200
For AI Inference: L4, A30, or H100 NVL config
For Visualization + AI: L40 / L40S, RTX 6000 Ada, A40
For Edge AI: Jetson Orin modules
NVIDIA GPUs - Save Up To 80%
✔️ 5-Year Warranty – No Risk: Pay Only After Testing