Instant Deployment
Launch A2 GPU clusters globally for lightweight AI workloads in seconds.
The NVIDIA A2 is the ideal entry-level GPU for businesses beginning their AI journey—delivering efficient performance for inference, computer vision, chatbots, analytics dashboards, and edge AI workloads at an unbeatable price.
16 GB GDDR6 Memory
Up to 4.5 TFLOPS
Up to 8.1 TFLOPS
200 GB/s
60W – Energy Efficient
Performance and flexibility for AI inference, media, and edge workloads — without the heavy price tag.
Launch A2 GPU clusters globally for lightweight AI workloads in seconds.
Run AI inference and video tasks at a fraction of the power used by data-center GPUs.
NVIDIA Tensor Cores accelerate FP16, INT8, and mixed-precision workloads efficiently.
From edge computing to AI-powered analytics, A2 GPUs are the perfect balance of affordability and AI capability — optimized for inference, cost-efficiency, and scale.
The A2 GPU delivers exceptional inference speed while consuming only 60W — ideal for continuous, real-time processing.
Deploy compact AI models at the edge or in the cloud with seamless scalability and consistent throughput.
Perfect for startups and businesses scaling from prototype to production without high infrastructure costs.
Run on Tier 3 data centers with guaranteed uptime, secure cloud architecture, and predictable billing.
Experience practical AI acceleration with A2 GPUs —engineered for always-on inference, computer vision, and edge workloads. Powered by Ampere Tensor Cores and 16 GB GDDR6 memory in a low-power 60 W profile, A2 delivers responsive performance while keeping energy usage and costs down. Scale horizontally across regions, serve models in real time with TensorRT/ONNX Runtime , and power media pipelines with NVENC/NVDEC —all on inhosted.ai’s secure cloud with 99.95% uptime and predictable pricing.
No middlemen. No shared footprints. End-to-end control of power, cooling, networking and security—so your AI workloads run faster, safer, and more predictably.
A2 GPUs redefine affordability and reliability for AI acceleration — designed for inference, automation, and real-time analytics at scale.
Faster AI inference compared to traditional CPU-based systems
Lower energy consumption vs high-end GPUs
Better cost-to-performance ratio for small AI models
Uptime backed by Inhosted.ai Tier 4 infrastructure
Where NVIDIA A2 transforms performance into productivity — ideal for small-scale AI, edge, and enterprise automation.
Deploy chatbots, recommendation systems, and speech recognition models with low latency and minimal energy usage.
Run object detection, surveillance analytics, and image processing models efficiently at the edge.
Accelerate media workflows and reduce CPU load during 4K video streaming or compression.
Perform real-time predictions in manufacturing, logistics, and retail environments with compact AI nodes.
Boost BI dashboards and analytics workloads using GPU-accelerated computations for faster insights.
Deploy small transformer-based models for text classification, summarization, and automated workflows.
At inhosted.ai, we empower AI-driven businesses with enterprise-grade GPU infrastructure. From GenAI startups to Fortune 500 labs, our customers rely on us for consistent performance, scalability, and round-the-clock reliability. Here's what they say about working with us.
Join Our GPU Cloud"We started with A2 GPUs to deploy our chatbot system — performance exceeded expectations. The latency was near real-time, and costs were 40% lower than other GPU providers."
"The A2 instances from inhosted.ai gave us an affordable way to test AI inference pipelines before scaling to A100. Perfect for startups and R&D workloads."
"For image classification tasks, A2 GPUs hit the sweet spot — efficient, stable, and economical. The support team was always quick and helpful."
"We run multiple lightweight AI models across retail stores using A2 clusters. The uptime and performance have been flawless — a truly reliable edge solution."
"A2 GPUs allowed us to deploy scalable inference services at 1/5th the cost of premium GPUs. The pay-as-you-go model makes it easy to manage budgets."
"From setup to deployment, everything was straightforward. The A2 GPUs perform better than expected for NLP inference — fast, consistent, and budget-friendly."
"We run multiple lightweight AI models across retail stores using A2 clusters. The uptime and performance have been flawless — a truly reliable edge solution."
"A2 GPUs allowed us to deploy scalable inference services at 1/5th the cost of premium GPUs. The pay-as-you-go model makes it easy to manage budgets."
"From setup to deployment, everything was straightforward. The A2 GPUs perform better than expected for NLP inference — fast, consistent, and budget-friendly."
"We started with A2 GPUs to deploy our chatbot system — performance exceeded expectations. The latency was near real-time, and costs were 40% lower than other GPU providers."
"The A2 instances from inhosted.ai gave us an affordable way to test AI inference pipelines before scaling to A100. Perfect for startups and R&D workloads."
"For image classification tasks, A2 GPUs hit the sweet spot — efficient, stable, and economical. The support team was always quick and helpful."
The A2 GPU is designed for AI inference, video analytics, and edge deployments — delivering excellent performance at low power and cost.
While H100/H200 are built for large-scale AI training, the A2 is optimized for lightweight inference and real-time applications, offering a low-power, cost-effective alternative.
Yes. You can deploy multiple A2 GPUs for horizontal scaling of inference workloads, with load balancing and parallel compute efficiency.
The A2 GPU operates between 40–60W, providing excellent performance per watt for 24/7 AI operations or continuous edge inference.
The A2 supports all major AI frameworks — including TensorFlow, PyTorch, ONNX Runtime, and NVIDIA TensorRT, making it easy to deploy existing models.
inhosted.ai provides secure Tier 3 data centers, 99.95% uptime, and transparent pricing — making it the ideal platform for running cost-efficient GPU workloads globally.