Secure GPU Colocation for Enterprise AI & HPC

GPU Colocation
in India for AI, ML & HPC Workloads

  • GPU colocation in Tier III/IV facilities
  • High-density racks for H100, A100 and RTX
  • A+B power feeds with N+N backup
  • Carrier-neutral network with DDoS protection
  • Full control of hardware and CUDA stack
  • For AI startups, labs and enterprises
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H100, A100 & RTX ready · Tier III/IV · 24/7 expert support
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20kW+
Private Cage Power
Tier III/IV
Data Centers
N+N
Power Redundancy
24/7
Expert Support

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Choose your best GPU & High-Density Colocation plan

  • 24/7 NOC Support
  • Remote Hands Included
  • DDoS Protection Included
VyomCloud GPU and Server Colocation plans with rack space, power, network, bandwidth and monthly price in Indian rupees
Plan Rack Space Power Network Bandwidth Monthly Price (₹) Order Now
1U Server Colocation 1U 0.5 kW Power Included 1 Gbps Network Port 10 TB Bandwidth ₹5,251/mo Renews at the same price Get Now
Quarter Rack Colocation 10U 1.5 kW Power Included 1 Gbps Network Port 30 TB Bandwidth ₹17,711/mo Renews at the same price Get Now
Half Rack Colocation 21U 3 kW Power Included 10 Gbps Network Port 50 TB Bandwidth ₹31,061/mo Renews at the same price Get Now
Full Rack Colocation 42U 6 kW Power Included 10 Gbps Network Port 100 TB Bandwidth ₹57,761/mo Renews at the same price Get Now
42U High-Density GPU Rack 42U 12 kW Dual A+B Power 10 Gbps Network Port 200 TB Bandwidth ₹99,999/mo Renews at the same price Get Now
Private GPU Cage (20kW+) Multi-Rack Cage 20 kW+ High-Density Power 10G / 40G / InfiniBand Ready Custom Bandwidth ₹149,999/mo Renews at the same price Get Now

Typical GPU server footprints: Quarter Rack (1.5 kW) fits 1× dual-RTX/L40S inference node · Half Rack (3 kW) fits 1–2× 4-GPU A100/L40S servers · Full Rack (6 kW) fits 1× 8-GPU A100/H100 node + storage · 42U High-Density GPU Rack (12 kW) fits 2–3× 8-GPU A100/H100 nodes · Private GPU Cage (20 kW+) fits 4+ multi-GPU clusters with InfiniBand. Request a custom kW quote.

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Compare GPU Colocation with Other GPU Hosting Options

Not sure whether to colocate, rent a GPU server or use cloud GPUs? Here is how they differ. Our team can also help you choose based on your workload, budget and how long you plan to run it.

GPU colocation compared with a dedicated GPU server and cloud GPU
Your GPUs. Your Stack.

GPU Colocation

Dedicated GPU Server

Cloud GPU

Description You own the GPU servers; we host them We supply a physical GPU server for rent GPU capacity rented by the hour or month
Hardware Owner You own it Provider owns it Provider owns it
Control Level Full control from hardware to software Full control at OS level Limited to the instance
Cost Over Time Lower for steady, long-running workloads Predictable monthly cost Can climb quickly for constant use
Management You manage servers, we manage the facility You manage the OS and apps You manage workloads only
Best For Teams with their own GPUs and steady demand Teams that want GPUs without buying hardware Short experiments and variable demand
Choose Plan Get Now View GPU Servers View Cloud Servers

Still not sure which setup fits? Contact our team or use our Server Finder to receive a personalised recommendation in seconds.

Included on every plan · 1U to 20kW+ Private GPU Cages

Features of Every VyomCloud GPU Colocation Plan

Redundant power, cooling, security, and 24/7 support come standard. None of it is a paid add-on.

N+N Power Redundancy

Redundant A+B power feeds and backup systems keep your GPU nodes running through a utility or feed failure.

Performance

High-Density Power and Cooling

Racks are built for the heat and power draw of GPU servers, with up to 20kW+ available in private cages.

Performance

Tier III/IV Data Center

A facility built for continuous operation, with redundancy across power, cooling and network.

Security

Multi-Layer Physical Security

Biometric access control, CCTV, and 24/7 on-site monitoring protect your hardware.

Security

Carrier-Neutral Network

Choose your connectivity, with low-latency routes and options for private cross-connects.

Network

Always-On DDoS Protection

L3–L7 filtering absorbs floods before they reach your inference endpoints and APIs.

Network

Remote Hands

30 minutes included each month for reboots, drive swaps, and cable checks, with more hours available on demand.

Support

24/7 Expert Support

Engineers who work with GPU and data center infrastructure every day respond to your tickets.

Support

Real-World Use Cases of GPU Colocation

GPU colocation is a practical choice once your workload is steady and your hardware bill matters. Here are the most common ways businesses use it.

AI Model Training

Teams training large language models or vision models keep their H100 or A100 nodes running for weeks. Colocation gives them the power and cooling for that load without paying cloud GPU rates by the hour.

Production AI Inference

Run inference servers for chatbots, recommendation engines and search close to your users. Owning the hardware keeps cost per request predictable as traffic grows.

Machine Learning Research

Universities and research labs use colocation to host shared GPU clusters, with the power, cooling and connectivity a campus server room usually can't provide.

Generative AI Products

Startups building image, video or text generation tools host their own GPU fleet so they control cost, latency and data handling.

Rendering and VFX Pipelines

Studios place render nodes in colocation for 3D rendering, animation and visual effects, scaling up the rack count when a project demands it.

High-Frequency Trading and Quant Research

Trading firms host GPU servers for backtesting and real-time analysis where low latency and a reliable network matter.

Healthcare and Life Sciences Computing

Genomics, drug discovery and medical imaging need heavy parallel compute and tight control over sensitive data. Colocation lets you keep your hardware and your data in one governed location.

Data Analytics and Big Data Processing

Run GPU-accelerated analytics on large datasets, with fast local storage and a strong network link to your data sources.

Simulation and Engineering (HPC)

Engineering firms run CFD, financial and scientific simulations on GPU nodes that stay on around the clock.

Private AI for Regulated Industries

Banks, insurers and government-linked organizations keep AI workloads on hardware they own, inside an Indian facility, to meet data residency and audit needs.

Your GPUs. Your Stack. Our Data Center.

Why Choose VyomCloud for GPU Colocation?

Colocation built for the power, heat, and network demands of GPU infrastructure.

12 kW high-density cabinets and 20 kW+ private cages with redundant A+B power feeds and tuned hot/cold aisle containment keep H100, A100, and L40S nodes running without thermal throttling during multi-week training jobs.

GPU colocation facility with redundant power and tuned cooling Biometric access, CCTV and DDoS filtering for colocated GPU hardware Carrier-neutral connectivity for low-latency paths N+N redundancy for training jobs and production AI services

Why Businesses Choose VyomCloud for GPU Colocation Needs

You keep control of your GPU servers. We handle the building, the power, and the network.

01 · Pricing

Transparent and Fair

No hidden fees or surprise charges. The quote you accept is the price you pay, which makes it easier to plan infrastructure spend.

  • No hidden fees
  • Predictable monthly costs
01
02 · Cost

Lower Spend for Steady Workloads

When GPUs run most of the day, owning the hardware and colocating it often costs less than renting cloud GPUs. You stop paying hourly rates for capacity you use constantly.

  • Cost control for long-running jobs
  • No per-hour GPU charges
02
03 · Security

Enterprise-Grade Protection

Biometric access, CCTV monitoring and DDoS-protected networking give your hardware strong protection at every layer.

  • Multi-layer physical security
  • DDoS-protected network
03
04 · Reliability

Power and Network Redundancy

Redundant A+B power feeds, backup systems and resilient networking reduce single points of failure during maintenance or faults.

  • N+N power design
  • Resilient connectivity
04
05 · Support

Engineers on Site Around the Clock

Our team is in the facility 24/7 and backed by a 99.5% uptime SLA with credits if we fall short.

  • 24/7/365 on-site engineering
  • SLA credits when targets are missed
05

What Our Clients Say

Hear from AI labs, ML teams, and enterprises hosting GPU clusters with VyomCloud

Our cloud GPU bill was eating the grant. We bought two 8×A100 servers, placed them in a high-density rack with A+B power, and now run multi-week training jobs without watching an hourly meter.
Ankit Kumar Customer
We couldn't cool four H100 chassis in our office building. Moving them into a private cage solved the power and heat problem in one step, and the biometric access log satisfied our healthcare clients.
Nikhil Arora Customer
Our inference traffic runs 18 hours a day. Colocating our own L40S nodes cut our monthly compute spend by more than half compared to cloud GPUs, and remote hands swapped a failed NVMe drive for us within the hour.
Pooja Venkatesh Customer
We began with two RTX servers in a Half Rack and expanded to a full cabinet when our VFX pipeline grew. The team planned the move around our render queue so we didn't miss a delivery.
Rohit Bansal Customer
FAQ

GPU Colocation FAQs

Everything you need to know before you move your GPU servers into our data center.

GPU colocation means you place your own GPU servers in a third-party data center. You own and manage the hardware and software. The provider supplies rack space, power, cooling, network connectivity and physical security. It suits teams that need more power and cooling than an office can offer.

With colocation, you own the GPU servers and we host them. With a dedicated GPU server, we own the hardware and you rent it. Colocation fits teams that already have GPUs or want specific configurations. A GPU Server fits teams that want to start without buying hardware.

Our standard plans include 0.5 kW on 1U (suitable for a gateway or single low-power appliance), 1.5 kW on Quarter Rack (10U, suitable for 1× dual-RTX/L40S inference server), 3 kW on Half Rack (21U, suitable for 1–2× 4-GPU A100/L40S servers), and 6 kW on a standard Full Rack (42U, suitable for 1× 8-GPU A100/H100 node or 2–3× inference nodes). For dense AI training clusters, our 42U High-Density GPU Rack delivers 12 kW of A+B power (supporting up to 2–3× 8-GPU A100/H100 servers), and our Private GPU Cage supports 20 kW+ per rack footprint.

N+N means there are two full, independent sets of power equipment, each able to carry your whole load. If one set fails, the other takes over without interruption. For GPU training runs that last days or weeks, this protects you from losing progress to a power event.

Your equipment sits in a Tier III/IV facility with 24/7 security monitoring, biometric access control, and CCTV. Private cabinets and cages add another layer of separation. On the network, always-on DDoS protection filters attacks before they reach your servers.

Ship or hand-deliver your servers to our facility, and our team will rack, cable, and power them on. Before shipping, send us your hardware specs, power needs and network requirements so we can prepare your space. Our Migration team can also help move your data and workloads.

Yes. You manage your servers over the network with SSH, RDP or IPMI/BMC, the same way you would at your own site. For physical tasks, our on-site engineers step in through remote hands.

Standard colocation plans start at ₹5,251/mo for 1U (0.5 kW), ₹17,711/mo for a Quarter Rack (10U, 1.5 kW), ₹31,061/mo for a Half Rack (21U, 3 kW), and ₹57,761/mo for a standard Full Rack (42U, 6 kW). High-density GPU plans start at ₹99,999/mo for a 42U High-Density GPU Rack (12 kW A+B power) and ₹1,49,999/mo for a Private GPU Cage (20 kW+ high-density power). Send us your server specs and power draw for a tailored quote within two hours.

Cloud GPUs are flexible, but the cost adds up fast for workloads that run all day. With colocation, you buy the hardware once and pay only for space, power and connectivity. You also get full control over drivers, firmware and cluster design, and your data stays on hardware you own.

You can host NVIDIA H100, H200, A100, V100, L40S or RTX-class cards, as long as the server fits our power and cooling limits. If you are unsure about a specific model or chassis, send us the specs and we will confirm.

Tell us what your hardware needs, and we will check what our facility can support. Air-cooled GPU servers are standard, and we can discuss special cooling requirements for custom clusters.

We offer carrier-neutral connectivity, so you can choose your providers and set up private cross-connects. For multi-node training, we can discuss high-speed interconnects such as InfiniBand in private cage setups.

Yes. Every plan includes 30 minutes of remote hands each month for tasks like reboots, drive swaps, and cable checks. Extra hours are available whenever you need them.

Yes. Many customers begin with a half rack and a few GPU nodes, then move to a full cabinet or private cage as demand grows. We plan the expansion with you so your running jobs aren't disturbed.

Your hardware and data remain in our Indian data center, which helps with data residency and compliance needs. Talk to us about your audit or regulatory requirements, and we will share what documentation we can provide.

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