AI innovation in India is moving fast and it demands high-performance GPUs. The NVIDIA L40S, with Ada Lovelace architecture, a powerful universal GPU for AI and graphics workloads, has become the top choice for Indian teams tackling cutting-edge applications like generative AI, 3D rendering, simulation and scientific visualization.
As demand grows across AI labs, VFX studios and GenAI startups, you are weighing a critical decision on NVIDIA L40S price: Should you rent it from the cloud providers or buy and manage it on-prem?
If L40S utilization is consistently high, then owning will offer better ROI. However, renting will be ideal for unpredictable workloads, early-stage pilots, or establishing presence in multiple regions.
This blog breaks down the decision in practical terms, comparing retail prices, rental rates, operational costs, workload suitability and return on investment (ROI). If you’re evaluating high-performance GPUs, this guide will help you make an informed and financially sound choice.
What is NVIDIA L40S GPU?
The NVIDIA L40S is a powerful data center GPU built for demanding AI, graphics and simulation workloads. It offers up to 1.45 PFLOPS of FP8 performance and over 1,000 TOPS of INT8 throughput which make it well-suited for generative AI, large language models and immersive 3D experiences.
Image Source: NVIDIA L40S
The device features three NVENC encoders and three NVDEC engines for video processing acceleration. It has dedicated hardware for real-time ray tracing and ultra-quality rendering.
Moreover, L40S has 48 GB of GDDR6 memory, 864 GB/s of bandwidth and runs on a dual-slot PCIe Gen4 x16 interface with a 300 W TDP. So, it is an excellent option for high-throughput AI pipelines, real-time rendering, digital twins and production-scale inference where speed and visual quality are important.
Compared to the L40, the L40S offers higher AI and graphics performance. This is because of its better use of tensor cores and improved parallel processing. These upgrades lead to faster results, smoother rendering and better support for complex AI-graphics workflows.
What is the Buying Cost NVIDIA L40S?
When it comes to buying L40S 48 GB, it typically falls between ₹7,50,000 to ₹8,00,000 from Indian resellers, inclusive of GST. This price includes a 3-year warranty via PNY and is fairly standard across PCStudio, SCL Gaming and other enterprise partners.
But that’s just the beginning. Deploying the L40S on-prem means provisioning compatible chassis (U-series servers or high airflow racks), power supplies (at least 850W gold or platinum-rated) and cooling.
So, you can expect to budget an additional ₹1.5–₹2 lakh per unit. Stock lead times vary from 2 to 6 weeks depending on inventory and import cycles, which can delay ramp-ups.
Operationally, you’ll need to factor in power, cooling, hosting, hardware monitoring and firmware updates. But you get full control, low latency and potentially lower long-term costs if utilization is high.
What are the Current Rental Prices of L40S GPU?
Here’s a quick look at current NVIDIA L40S GPU rental rates in India across major cloud providers.
- AceCloud offers NVIDIA L40S GPU rental starting at ₹123.29/hour, with structured monthly and term discounts.
- E2E Networks lists L40S at approximately ₹83/hour, with structured monthly and term discounts.
- Yotta Shakti Cloud offers L40S at ₹128/hour.
- Cyfuture Cloud offers L40S from approximately ₹102.24/hour.
- Among hyperscalers, AWS (G6 instances), Azure and Google Cloud (G2) offer L40S-enabled machines, with typical tracked on-demand rates ranging between ₹61–₹67/hour depending on the region and configuration. Availability in India varies and not all hyperscaler L40S SKUs are currently exposed in Mumbai or local zones.
Note: Prices fluctuate by region, commitments and spot availability, so you should validate your dates and zones.
The cheapest option isn’t always the best value. You need to factor in reliability, ease of use, human support and hidden costs like data transfer fees.
Which Workloads Make Renting Smarter than Buying and Vice Versa?
The best strategy depends largely on workload type, usage pattern and organizational maturity. Renting is ideal for AI labs and startups with bursty or exploratory GPU needs. If you’re testing models, experimenting with fine-tuning or running short inference cycles, renting gives you immediate access without the burden of capital expenditure or long-term infrastructure planning.
Use cases like large-scale inference pipelines, episodic rendering jobs or temporary simulation projects to benefit from the elasticity of cloud GPUs. For example, teams working with Llama-3 8B or similar LLMs often find that the L40S, especially in FP8 mode, offers up to 1.4x higher tokens/sec throughput than the A100, according to NVIDIA’s benchmarks. Renting allows you to scale horizontally across multiple L40S units without hardware procurement delays.
Conversely, if your workload involves continuous training, persistent multi-GPU workflows or require full-stack hardware control (e.g. for compliance), purchasing an L40S may be more appropriate. On-prem usage offers better latency control and can be cost-effective if GPUs are utilized 24×7 at high intensity.
What are the Key Factors to Consider While Buying or Renting L40S GPUs?
The demand for high-performance computing is growing rapidly in various industries such as AI and machine learning, 3D rendering and scientific simulations, GPUs such as NVIDIA L40S are getting more attention.
Whether you are buying or renting, the decision of which L40S GPU setup to go for should not be based on price alone. Here are a few key factors that you should evaluate.
1. Performance Requirements
Firstly, you should evaluate what work you have lined up for. The L40S is perfect for AI inference, training and graphics rendering at a high level. Essentially, if you handle large datasets or complex neural networks, the L40S fits well. However, if you have only light workloads, then it may be overkill. Make sure that your application is powerful enough to make use of the Tensor Cores and large memory capacity.
2. Cost and Budget Flexibility
The L40S GPUs are high-end and come with a premium price tag. Renting will probably be cost-effective only if your usage is for a short period of time or is project-based. Whereas, buying will make sense if you are going to have long-term and steady usage. Total ownership costs should also be factored in, such as maintenance, electricity and cooling costs.
3. Availability and Scalability
The problem with availability is that it can only be limited to a few units at most since these GPUs are in high demand. Thus, renting provides flexibility, which is perfect for scaling projects fast without an initial hardware outlay. For enterprises planning to scale AI operations, ensure the provider supports seamless upgrades or clustering options.
4. Infrastructure Compatibility
Check that your existing hardware, especially power supply, cooling devices and PCIe slots are up to par with the L40S. If the answer is no, you will have to make extra investments. However, with cloud-based rentals, you may be able to get around these issues, but there will still be costs to pay.
5. Vendor Support and SLAs
Reliable support cannot be taken for granted. While renting, it is prudent to check the provisions for uptime, maintenance and service level agreements (SLAs). When it comes to buying, the vendor you choose should provide warranty, driver updates and integration support.
Ready to Deploy the NVIDIA L40S?
As AI adoption grows rapidly in India, access to high-performance GPUs like the NVIDIA L40S has become essential for businesses and research teams. The key decision is not just about technical specifications or raw power, but how to deploy the GPU in a way that aligns with your project goals, budget and operational needs.
Buying the L40S is ideal for organizations with continuous GPU needs, compliance requirements or in-house infrastructure. It provides long-term value and direct control over latency and hardware. Renting is better suited for teams with temporary, project-based or bursty workloads. It offers flexibility, fast deployment and zero capital expenses.
AceCloud makes enterprise-grade computing accessible with competitive L40S rental options in India. With hourly pricing, structured monthly discounts and dedicated support, we help businesses avoid hardware delays and scale up faster.
Whether you are exploring a proof of concept or building a production-grade AI stack, AceCloud ensures you get the performance you need without unnecessary costs.
Get started today with AceCloud’s NVIDIA L40S offerings. Scale your AI without limits, avoid procurement delays and pay only for what you use.
Frequently Asked Questions:
Duty depends on HS code and current policy. Many teams avoid surprises by buying from Indian distributors with GST-inclusive invoices. If you import, have your broker model total landed cost and clearance timing.
Use the breakeven formula. In practice, the crossover often appears between 300 and 600 hours per month when amortization is 24 to 36 months and your fixed on-prem costs are modest. Your exact Rc, F, and tariff will shift this.
Multiple Indian resellers list the PNY L40S 48 GB at GST-inclusive prices. Get at least three quotes and confirm stock and warranty terms.
Yes, but price and speed to sell vary with global supply. If resale is part of your plan, document the decommissioning and data sanitization flow now, not later.
No, L40S doesn’t support MIG or NVLink. You can use MPS or Kubernetes plugins for partitioning instead.
