80GB HBM2e and high-speed bandwidth for faster AI training, large models, and scalable multi-GPU workloads.
HBM2e VRAM
Training Ready
Fast Launch
Pricing
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Architecture
GPU Memory
Memory Bandwidth
TF32 Tensor
FP16 Tensor
FP32 Performance
Interconnect
Form Factor
Same NVIDIA GPUs, lower spend, India-first regions and 24/7 human support.
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What Matters
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BTrack
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Hyperscalers
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GPU Pricing
Cost structure
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Monthly plans with up to 60% savings. | Higher long-term flat yearly rate. |
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Billing & Egress
Transparency
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Simple bill with predictable egress. | Many line items and surprise charges. |
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Data Location
Regional presence
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India-first GPU regions, low latency | Fewer India GPU options, higher latency/cost. |
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GPU Availability
Access to capacity
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Capacity planned around AI clusters. | Popular GPUs often quota-limited. |
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Support
Help when you need it
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24/7 human GPU specialists. | Tiered, ticket-driven support; faster help extra. |
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Commitment & Flexibility
Scaling options
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Start with one GPU, scale up. | Best deals need big upfront commits. |
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Open-source & Tools
Ready-to-use models
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Ready-to-run open-source models, standard stack. | More DIY setup around base GPUs. |
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Migration & Onboarding
Getting started
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Guided migration and DR planning. | Mostly self-serve or paid consulting. |
Train complex AI models faster with NVIDIA A100 GPUs and high-throughput performance.
Run multiple AI models efficiently with low-latency inference and reliable throughput for production.
Accelerate data analytics, processing, and ML pipelines with powerful A100 compute and memory.
Accelerate scientific workloads with high-speed computing and GPU memory for demanding simulations.
Run multiple workloads simultaneously with A100 virtualization.
Handle training, inference, analytics, and batch jobs on the same A100 infrastructure.
Scale AI and HPC applications with reliable A100 compute for demanding workloads.
Power intensive model development with fast compute and large-scale GPU memory.
Talk to us to find out how we can help you achieve your IT objectives with the utmost security and peace of mind.
We stay ahead of curve, leveraging cutting-edge technologies and strategies to remain competitive. Explore our frequently asked questions below for quick guidance.
NVIDIA A100 is a data-center GPU built on the Ampere architecture for AI training, inference, high-performance computing, data analytics, and other demanding accelerated workloads.
Yes. A100 provides high compute performance, large HBM2e memory capacity, and high memory bandwidth, making it suitable for training, fine-tuning, and inference of large language and deep learning models.
NVIDIA A100 is available with up to 80GB HBM2e memory and up to 2TB/s memory bandwidth, along with Tensor Cores and Ampere architecture for AI and HPC acceleration.
Yes. A100 is designed to handle both high-volume AI inference and compute-intensive HPC workloads, including scientific simulations, data analytics, deep learning, and large-scale numerical processing.
Yes. Btrack India provides NVIDIA A100 GPU infrastructure for businesses, developers, and research teams that need scalable resources for AI, machine learning, inference, and HPC workloads.
Yes. A100 GPU infrastructure can be used for short-term development, model training, testing, proof-of-concept projects, and temporary compute requirements without purchasing dedicated hardware.
Yes. Multiple NVIDIA A100 GPUs can be combined for distributed AI training, large-model workloads, HPC applications, and other compute-intensive tasks requiring additional GPU capacity.
A100 pricing varies based on GPU configuration, server resources, rental duration, and deployment requirements. Contact BTrack India for current NVIDIA A100 rental pricing and availability.
