Launch Training Pipelines Fast
Spin up A100 clusters for LLMs, recommenders, and multimodal workloads — with autoscaling, spot-aware scheduling, and template-based jobs for repeatable experiments.
Cloud GPU Platform
Starting from ₹170.00
NVIDIA A100 Cloud GPUs — Unified Acceleration for AI, Data, and HPC
NVIDIA A100 GPUs bring unified acceleration for AI, data, and HPC workloads — enabling you to train and fine-tune large language models, run multimodal AI, and power data-intensive pipelines with proven enterprise-grade stability. Built on the Ampere architecture with high-bandwidth HBM2e memory and NVLink support, A100 delivers exceptional performance for LLMs, recommendation engines, analytics, and large-scale scientific computing.
NVIDIA A100 GPU Technical Specifications
VRAM
80 GB HBM2e with ECC
Tensor Performance (FP16)
1,248 TFLOPS
Compute Performance (TF32)
Up to 624 TFLOPS
Memory Bandwidth
2.0 TB/s
NVLink / Interconnect
600 GB/s Bidirectional (per GPU, NVLink)
The foundation for faster, smarter AI deployment
Performance, agility and predictable scale — without the DevOps drag.
Throughput-Optimized Storage
Distributed I/O tuned for large batch sizes and streaming ETL. Feed A100s at line-rate for stable training curves and high-QPS inference.
Enterprise Controls
Role-based access, GPU quotas, audit logs, and secrets management — all designed for secure, collaborative AI teams shipping models to production.
Why Businesses Choose Inhosted.ai for NVIDIA L40S GPUs
From large-scale model training to cost-efficient inference, enterprises choose Inhosted.ai for A100 clusters that are optimized for consistent throughput, transparent billing, and uptime at scale — all delivered on secure, compliance-ready infrastructure.
Proven Performance for Enterprise AI
Run billion-parameter models, recommendation engines, and embeddings at predictable speed. The A100 balances compute density with memory bandwidth to deliver stable iterations, fast convergence, and lower cost per experiment.
Built for Full-Stack AI Workflows
Orchestrate end-to-end pipelines — data prep, pretrain, fine-tune, and batch inference — using CUDA, cuDNN, TensorRT, Triton, and the PyData ecosystem. One cluster, many workloads.
Security & Compliance at the Core
Each deployment runs in ISO 27001 and SOC-certified facilities with encryption at rest and in transit. Network segmentation, per-tenant isolation, and hardened images keep data secure across teams and projects.
Global Regions & Predictable Scale
Deploy where your users are. Inhosted.ai offers multi-region availability with automated failover, steady latency, and a 99.95% uptime SLA — so your training and inference stay uninterrupted.
Ampere Architecture
NVIDIA A100 GPU Servers, Built for Performance and Scale
Run state-of-the-art AI and HPC on NVIDIA A100 — unifying training, inference, and analytics on a single architecture. With 80 GB HBM2e, high-bandwidth NVLink, and Multi-Instance GPU (MIG) support, A100 delivers exceptional utilization across teams and workloads. Perfect for data science platforms, enterprise AI, and research environments that need consistent throughput, flexible scheduling, and production-grade reliability.
You know the best part?
We operate our own data center
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.
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Lower, predictable costs Direct rack ownership, power & cooling optimization, no reseller markups.
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Performance we can tune Network paths, storage tiers, and GPU clusters tuned for your workload.
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Security & compliance Private cages, strict access control, 24×7 monitoring, and audit-ready logs.
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Low-latency delivery Edge peering and smart routing for sub-ms hops to major ISPs.
99.99%Uptime SLA
Tier IIIDesign principles
Multi-100GBackbone links
24×7NOC & on-site ops
Breakthrough AI Performance
The NVIDIA A100 sets the benchmark for versatile, data-center AI — accelerating training, inference, and analytics with outstanding efficiency. Experience faster time-to-accuracy, better memory bandwidth utilization, and elastic scaling across clusters with MIG and NVLink-enabled topologies.
4×
Faster model training vs previous gen on mixed precision
7×
Higher inference throughput with MIG partitioning
80GB
High-bandwidth HBM2e for large batch sizes
99.95%
Uptime on Inhosted.ai GPU cloud
Top NVIDIA A100 GPU Server Use Cases
Where the NVIDIA A100 transforms workloads into breakthroughs — from LLM training to scientific computing, accelerating results that redefine performance limits.
AI Model Training
A100 GPUs deliver enterprise-grade throughput for LLMs, vision models, and multimodal training. Mixed-precision Tensor Cores enable fast, stable training with large batch sizes and high memory bandwidth — ideal for teams optimizing time-to-accuracy.
Real-Time Data Analytics
Power batch and streaming analytics with GPU-accelerated ETL, SQL, and feature engineering. A100’s parallelism unlocks low-latency dashboards, anomaly detection, and predictive insights that keep operations moving at peak efficiency.
High-Performance Computing (HPC)
A100 combines FP64 compute and Tensor Cores to accelerate simulations, optimization, and scientific workflows. Perfect for climate modeling, CFD, molecular dynamics, and large-scale research where precision and throughput both matter.
Natural Language Processing
Train and fine-tune transformer models efficiently. With strong memory bandwidth and Tensor Core acceleration, A100 shortens iteration cycles for translation, summarization, and RAG pipelines — and serves models with predictable latency.
Computer Vision & Generative Media
Speed up diffusion, detection, and video processing using CUDA-accelerated libraries. A100 sustains high-throughput image and video pipelines for content generation, understanding, and real-time processing at production scale.
Recommenders & Personalization
Run large embeddings, ANN/vector search, and multi-task recommenders. A100 accelerates ranking, retrieval, and personalization end-to-end — powering CTR improvements and highly relevant user experiences.
Trusted by Innovators
Building the Future
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
Aldo P.
★★★★★
✔ Verified Testimonial
"inhosted.ai helped us move GPU workloads in seconds. Uptime has been rock-solid, and performance consistent across regions — exactly what we needed for live inference."
Neha B.
★★★★★
✔ Verified Testimonial
"Best experience we’ve had with GPU cloud. Instant spin-ups, clear billing, and quick support. Our vision models deploy faster and stay within budget."
Rahul S.
★★★★★
✔ Verified Testimonial
"We run multi-region inference and scheduled retraining on inhosted.ai. Scaling from 10 to 400+ GPUs takes minutes, networking is consistent, and storage hits the throughput we need."
Leena G.
★★★★★
✔ Verified Testimonial
"Training times dropped and costs stayed predictable. The support team was proactive throughout deployment."
Aarav D.
★★★★★
✔ Verified Testimonial
"Migrating our LLM training stack to inhosted.ai gave us a 3× throughput boost. H100 clusters came online in seconds and billing stayed predictable. We cut project timelines by weeks."
Priya M.
★★★★★
✔ Verified Testimonial
"Predictable pricing, high GPU availability, and fast storage — we ship models faster with fewer surprises."
Leena G.
★★★★★
✔ Verified Testimonial
"Training times dropped and costs stayed predictable. The support team was proactive throughout deployment."
Aarav D.
★★★★★
✔ Verified Testimonial
"Migrating our LLM training stack to inhosted.ai gave us a 3× throughput boost. H100 clusters came online in seconds and billing stayed predictable. We cut project timelines by weeks."
Priya M.
★★★★★
✔ Verified Testimonial
"Predictable pricing, high GPU availability, and fast storage — we ship models faster with fewer surprises."
Aldo P.
★★★★★
✔ Verified Testimonial
"inhosted.ai helped us move GPU workloads in seconds. Uptime has been rock-solid, and performance consistent across regions — exactly what we needed for live inference."
Neha B.
★★★★★
✔ Verified Testimonial
"Best experience we’ve had with GPU cloud. Instant spin-ups, clear billing, and quick support. Our vision models deploy faster and stay within budget."
Rahul S.
★★★★★
✔ Verified Testimonial
"We run multi-region inference and scheduled retraining on inhosted.ai. Scaling from 10 to 400+ GPUs takes minutes, networking is consistent, and storage hits the throughput we need."
Frequently Asked Questions
What is the NVIDIA A100 GPU and why is it popular for enterprises?
The A100 is NVIDIA’s data-center workhorse built on the Ampere architecture. It unifies training, inference, and HPC so teams can run end-to-end AI pipelines on a single platform. With 80 GB HBM2e, Tensor Cores, and NVLink, it’s trusted by enterprises and research labs for reliability and performance across a wide range of workloads.
Where does A100 fit compared to H100 or L40S?
H100 pushes the absolute frontier for very large training runs, while L40S excels at AI inference plus graphics/visual workloads. A100 sits in the middle — incredibly versatile for both training and inference, with strong price-performance for companies that need one cluster to do many jobs well.
Can A100 handle both batch training and real-time inference?
Yes. A100 is designed for hybrid use. You can train during the day and run batch or real-time inference at night, or use MIG to partition a single GPU into multiple isolated instances — ideal for serving many models concurrently.
What performance characteristics matter most on A100?
High memory bandwidth, optimized Tensor Core math (TF32/FP16), and NVLink scaling are the big levers. Together they enable large batch sizes, stable step times, and fast multi-GPU training — all while maintaining predictable inference throughput.
How scalable are A100 clusters on inhosted.ai?
Very. You can scale from a few GPUs to large multi-node clusters with automated orchestration, elastic quotas, and regional placement. Our team helps you select NVLink/NVSwitch topologies when inter-GPU bandwidth is critical.
What about security and compliance?
Deployments run in ISO 27001 and SOC-certified environments with encryption in transit and at rest. We enforce workload isolation, private networking, and auditability so regulated industries can run safely.
Why deploy A100s with inhosted.ai instead of self-hosting?
You get ready-to-run clusters, predictable pricing, real-time GPU telemetry, and a 99.95% uptime SLA — without spending months on infrastructure. Our platform abstracts the heavy lifting so your teams ship models faster and focus on outcomes, not servers.