NVIDIA L4 GPU servers in India
One, two or four NVIDIA L4 GPUs in Mumbai, from ₹37,499/month. Built for inference — chatbots, speech, OCR and video — with 24 GB per GPU, your data in India and a GST invoice in rupees.
- GPU
- 1× NVIDIA L4 24 GB
- vCPU
- 8
- RAM
- 32 GB
- Storage
- 100 GB NVMe
- Since 2006, Jaipur
- 3,500+ businesses served
- Mumbai data centre, Yotta NM1
- GST invoice in INR
Who the L4 is for
For you if: You run AI in production — a chatbot or assistant on an open model of up to about 8 billion parameters, speech-to-text, OCR, embeddings and search — or video work such as transcoding and analytics, and you want it on a GPU in India, billed monthly in rupees.
Not for you if
- Your model needs more than 24 GB on one card — a 70B model, say → RTX PRO 6000 or H200
- You want full fine-tuning, or training beyond a small model → H200
- You need a GPU for a few hours a week → ask about hourly billing (on request)
NVIDIA L4 plans
| Plan | GPU | vCPU | RAM | Price | Enquire |
|---|---|---|---|---|---|
L4 ×1 · 8 vCPU | 1× NVIDIA L4 24 GB | 8 | 32 GB | ₹37,499 a month, ex-GST | Ask |
L4 ×1 · 16 vCPU | 1× NVIDIA L4 24 GB | 16 | 64 GB | ₹40,699 a month, ex-GST | Ask |
L4 ×2 · 16 vCPU | 2× NVIDIA L4 48 GB | 16 | 64 GB | ₹69,999 a month, ex-GST | Ask |
L4 ×2 · 32 vCPU | 2× NVIDIA L4 48 GB | 32 | 128 GB | ₹80,099 a month, ex-GST | Ask |
L4 ×4 · 32 vCPU | 4× NVIDIA L4 96 GB | 32 | 128 GB | ₹1,38,499 a month, ex-GST | Ask |
L4 ×4 · 64 vCPU | 4× NVIDIA L4 96 GB | 64 | 256 GB | ₹1,59,299 a month, ex-GST | Ask |
Prices a month in INR, exclusive of 18% GST. Every plan includes 100 GB of NVMe storage, 10 TB of transfer a month and one IPv4 address. Hourly billing: on request. Renews at the same price.
What every L4 plan includes
- One, two or four NVIDIA L4 GPUs, each with 24 GB of memory
- The whole GPU is assigned to your server, and no one else's work runs on it.
- 100 GB of NVMe storage and 10 TB of transfer a month
- One IPv4 address, and root access to the server
- GPU drivers, CUDA and PyTorch installed on request, at no extra charge
- Servers in Mumbai: your models and data stay in India
Add-ons
| More NVMe storage | price on request |
| Additional IPv4 | price on request |
| Drivers, updates and monitoring done for you | quoted |
| Scheduled off-server backups | see cloud backup |
What we do, what you do
| Task | We do | You do |
|---|---|---|
| GPU hardware, network and power; replacing failed parts | ||
| Installing the operating system | ||
| GPU drivers, CUDA and PyTorch | on request | keeping them updated |
| Security updates and firewall | ||
| Monitoring GPU use and health | ||
| Backups of models and data | ||
| Your models, code and data |
What the L4 is good at
- 24 GB of GPU memory
- Enough for an open model of about 8 billion parameters at 16-bit, with room for context, or larger models at 8-bit or 4-bit. Allow about 2 GB per billion parameters at 16-bit, and roughly half that at 8-bit.
- 8-bit (FP8) support
- The L4's AI cores work in 8-bit (FP8) directly, so a model quantised to 8-bit needs half the memory of 16-bit.
- Video engines
- Two hardware encoders and four decoders, with AV1, handle transcoding and video analytics in circuits separate from the ones that run AI.
- One, two or four GPUs
- More GPUs let you run several models side by side, or serve more users. Splitting one model across cards works but costs some speed; for one model over 24 GB, compare the RTX PRO 6000's 96 GB on a single card.
- vCPU and RAM
- The processor and memory around the GPU, for loading data, preparing it and answering requests. The larger options suit busy APIs and pipelines that prepare a lot of data.
What happens after you say yes
- same dayTell us the model and the traffic; we check it fits and that the GPU is in stock
- Usually the same working day, when the GPU is in stockInvoice sent; server set up in Mumbai with root access
- when you're readyYou load your model and go live — or we move your setup from another provider
- 24/7GPU or hardware problem: call our toll-free number in India
In Mumbai, supported from Jaipur
The L4 servers run in Mumbai, so the data your models read stays in India and answers reach users across India quickly. Support comes from our team in Jaipur, in English and Hindi, in IST, by WhatsApp, phone and email, and the invoice is in rupees with GST.
Moving an inference server from another provider, or from AWS or Azure? We set up the L4 server, copy your models and data, and test them before you switch. How migration works
Questions people ask
What is the NVIDIA L4 good for?
NVIDIA builds it for efficient video, AI and graphics. In practice: running AI models of small to medium size — chatbots, speech-to-text, OCR, embeddings and search — and transcoding or analysing video. It's a low-power card (72 watts), suited to serving models rather than training large ones.
Which models fit on one L4?
With 24 GB: an open model of about 7–8 billion parameters at 16-bit, with room for context; around 13 billion at 8-bit; and larger models at 4-bit. Long conversations need more memory for context, so leave headroom.
How much does an L4 cost per hour?
Our plans are monthly: one L4 at ₹37,499/month works out to about ₹51 an hour if it runs all month (730 hours). Hourly billing for short jobs: on request.
Can I fine-tune on an L4?
Small models, yes, with LoRA or QLoRA methods that cut the memory needed — QLoRA's authors fine-tuned a 65-billion-parameter model on one 48 GB GPU. Full fine-tuning needs roughly nine times the memory of running a model; for that, look at the H200.
Should I take one L4, two or four?
One per model is the simple rule. Take two or four to run several models side by side, or to serve more users with copies of the same model. If a single model won't fit in 24 GB, one card with more memory is usually faster than splitting it.
Is the GPU shared with anyone?
The whole GPU is assigned to your server, and no one else's work runs on it.
Do you install CUDA and PyTorch?
Yes, on request — the GPU drivers, CUDA and PyTorch, at no extra charge. You have root access, so you can add anything else: vLLM, Ollama, Triton or your own stack.
How quickly can I get an L4 server?
Usually the same working day, when the GPU is in stock. GPUs sell out, so we confirm the one you want is available before we send the invoice.
Tell us the model. We'll check it fits.
Model, users and hours a day — we'll tell you whether one L4 is enough, and which plan to take.
Support 9 am – 7 pm IST. Server-down issues are answered 24/7, in English and Hindi.
Tell us what you run and we'll reply with one recommendation.
No sequence, no sales calls. One reply from an engineer, within working hours.