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When it comes to high‑performance server and cloud infrastructure for AI, data analytics, or large‑scale rendering, choosing the right GPU makes a major difference. The NVIDIA L40S is emerging as one of the go‑to accelerators for enterprises in India that are deploying cloud hosting, server racks and modern data‑centre workloads. According to NVIDIA, the L40S delivers up to 1,466 TFLOPS in FP8 performance, making it well‑suited for tasks like generative AI, large language models, and heavy graphics workloads.
For Indian businesses, the question isn’t just “what performance does it deliver?” but also “what’s the actual price in India?” — because upfront investment, import duties, infrastructure support and total cost of ownership (TCO) all play into the business decision. In this blog, we’ll walk through the full price breakdown of the NVIDIA L40S in India, show the rent vs purchase options, highlight hidden costs, and give strategic guidance for businesses evaluating this GPU in the context of cloud hosting, server deployments, and data‑centre infrastructure.
Before diving into pricing, let’s set the context. The NVIDIA L40S is a data‑centre‑grade GPU built for high‑intensity workloads. It features 48 GB of GDDR6 memory, a high memory bandwidth (864 GB/s), and supports advanced Tensor and RT cores.
Why does that matter for cloud and server use?
- Businesses deploying scalable cloud hosting platforms or server racks often need GPUs that can handle both AI training and inference, plus graphics/visualisation tasks.
- Data‑centre deployments in India must factor in rack power, cooling, networking, data localisation and uptime — the L40S fits into these infrastructure stacks.
- For enterprises running 24x7 workloads or offering GPU‑as‑a‑service in Indian data centres, having a GPU with strong performance per watt, high memory and broad workload support is a big advantage.
So when you see the price, it isn’t just the card itself — it’s part of a broader decision about servers, racks, cloud hosting, and infrastructure.
Here are recent purchase‑price data points for the L40S in India:
- One reseller lists the NVIDIA L40S at ₹6,78,500 (ex‑tax) in India.
- Another listing shows ~ ₹7,49,950 (incl. taxes) for the PNY version of the L40S 48 GB.
- A more premium listing shows ~ ₹9,18,198.93 for the L40S from another retailer. (the exact model/config may vary)
- Some blogs quote “starting at approximately ₹4,50,000” in India for the L40S, but note they qualify this with “may vary based on configuration and seller”.
- For an Indian business buying the GPU hardware alone, expect a ball‑park range between ~ ₹6–9 lakhs for the L40S 48 GB, depending on the vendor, configuration, demand, and import taxes.
- The quoted “starting at ~₹4.5 lakhs” figure appears optimistic and may reflect limited stock or promotional pricing, so treat it with caution.
- Keep in mind: hardware cost is just the beginning — you’ll also need server chassis, cooling, rack space, power provisioning, possibly custom firmware/driver support, and ongoing maintenance.
Infrastructure cost: installing a high‑density GPU rack means higher power draw (300‑350W+ per GPU plus overhead), advanced cooling, redundant power supplies.
Operational expenses (OpEx): electricity, cooling, maintenance, technician time, licensing (vGPU, AI frameworks).
Depreciation and obsolescence: GPUs evolve fast; what you buy today may become second‑tier in a couple of years.
Import duties and supply chain: If hardware is imported, duties, freight, GST all affect final cost.
Rack/hosting costs: If you colocate in a data‑centre rather than on‑premises, you’ll pay for space, power, network bandwidth.
For many businesses the key question becomes: “Will the purchase make sense or is renting/hosting in a cloud/data‑centre better?”
Renting or leasing the L40S via a cloud hosting provider or GPU‑as‑a‑service model can dramatically reduce upfront cost and shift it into a more flexible expense.
Here are rental price data points:
- One Indian provider shows L40S hosting/rental at approximately $0.69/hour (~ ₹60/hour depending on exchange rate) in India.
- An international provider (for global usage) lists on‑demand pricing of US $1.29/hour and committed 36‑month pricing at US $0.89/hour.
- At ₹60/hour, if a business uses the GPU 24 hours a day for 30 days, cost ~ ₹43,000 in one month.
- Compare that to purchasing hardware for ~ ₹700,000 plus infrastructure + ongoing costs — renting may be more cost‑effective for variable workloads.
- If you commit to long‑term usage, providers may offer discounted rates (volume, reserved instances) which reduce hourly cost further.
- Workloads are bursty or temporary (AI training runs, prototyping, rendering batches).
- You want minimal upfront hardware cost and can scale down as needed.
- You prefer the provider handles hardware, cooling, power, networking, and support — you focus on your application.
- You need access to the latest GPU generation without worries about obsolescence or resale.
- You have consistent, high‑utilisation GPU workloads 24×7 for months/years.
- You have existing data‑centre or colocation infrastructure and want full control over hardware.
- You can amortize cost over years and long‑term TCO works in your favour.
Here’s a simplified comparison of owning vs renting for a business in India:
|
Scenario |
Purchase Model |
Rental Model |
|
Up‑front cost |
~₹6‑9 lakhs for GPU + server/infra |
Minimal – pay‑as‑you‑go (₹60/hr approx) |
|
Monthly cost (if running 24×7) |
Power + cooling + rack + network + amortised cost |
~₹43,000/month at ₹60/hr (assuming full use) |
|
Flexibility |
Low — hardware fixed |
High — scale up/down quickly |
|
Maintenance & infrastructure |
Managed by business |
Managed by provider |
|
Long‑term cost advantage |
Potentially better if very high utilisation |
Better if utilisation is variable or short‑term |
|
Control & customisation |
Full control over hardware, config |
Provider managed, less customisation |
For example: if you rent for 6 months at ₹43K/month = ₹2.58 lakhs. If you buy + infrastructure and run for 2‑3 years, you may amortize cost and get better cost per compute unit — but only if utilisation is consistently high.
Since India’s enterprise landscape is rapidly adopting cloud hosting, server racks and data‑centre infrastructure, businesses should weigh the following:
1. Workload Profile – Is it short‑term (training batches) or long‑term (inference service)?
2. Infrastructure Readiness – Do you have onsite racks/power/cooling or will you colocate/host via a provider?
3. Scalability Requirements – Will you scale GPU count quickly? Renting gives more agility.
4. Budget and CapEx vs OpEx Preference – Startups may prefer OpEx (renting) while large enterprises may justify CapEx.
5. Data‑centre Location & Latency – Hosting in India matters for latency, data locality and cloud hosting integration.
6. Vendor & Support Ecosystem – Ensure the provider offers Indian data‑centre hosting, GPU rental, or reseller stock with warranty.
7. Break‑Even Analysis – Calculate when owning becomes cheaper than renting based on utilisation hours and cost assumptions.
For Indian businesses evaluating the NVIDIA L40S GPU for cloud hosting, server infrastructure or data‑centre deployment, the price breakdown shows a clear trade‑off.
- If you purchase the hardware, expect ₹6‑9 lakhs for the card alone, and then add infrastructure, power, cooling, maintenance and ongoing costs.
- If you rent via a cloud hosting or GPU server provider, you can access similar performance for ~ ₹60/hr (or more depending on provider) and pay only for what you use.
- Renting is an excellent option for variable or bursty workloads, startups, prototyping, or when you want minimal Up‑front cost.
- Ownership makes sense when you have predictable, high utilisation, existing infrastructure and want full control and long‑term cost efficiency.
In short: the right choice depends on your business model, workload pattern, budget, and infrastructure readiness. The L40S is a high‑end GPU with huge capability — pairing it with the right deployment strategy (cloud hosting, server racks, data centres) will determine whether the investment yields optimal business value.
Let’s talk about the future, and make it happen!
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