The L4 is NVIDIA's low-power universal accelerator: 24 GB of GDDR6, FP8 Tensor Cores and AV1 media engines in a 72 W, single-slot card. It serves chatbots, recommendation and vision models, and transcodes hundreds of video streams — at a fraction of the power and price of larger GPUs. Start with one L4, then scale out with more instances behind a load balancer or Kubernetes as traffic grows.
QUICK ANSWER · UPDATED SEPTEMBER 2026
What Is The NVIDIA L4 GPU And When Should I Use It?
The NVIDIA L4 is a 72 W Ada Lovelace GPU with 24 GB of GDDR6, FP8 Tensor Cores and AV1 media engines, built for efficient AI inference, video processing and edge workloads. Choose it for always-on inference and video services; choose L40S or A100/H100 for heavier generative AI or training. XcellHost rents it in India from ₹36,700 a month (excl. GST).
KEY TAKEAWAYS
About 3.7× the FP16 Tensor throughput of a T4
72 W — lowest cost per inference for always-on services
AV1 encode and decode for dense video workloads
24 GB fits 7B–13B models quantised
Best for:AI inferenceVideo analyticsTranscodingEdge AI
Flexible plans for every workload
L4 Cloud GPU Plans
Select your billing period and choose the GPU configuration that fits your team. Prices start at ₹36,700/month.
For single users & PoC · 1 GPU
1×
L4GPU Cloud Lite
Server Type
Dedicated GPU VM
GPU
1 × 24 GB
Virtual CPU
8 vCPU
Memory
32 GB
NVMe Storage
500 GB
Network Port
1 Gbps
Dedicated IP
1
Operating System
Ubuntu 22.04 / Win Server 2025
Drivers
CUDA pre-installed
Protection
Virtual Firewall + Anti-DDoS
Endpoint Security
Acronis Cyber Protect Cloud
Support
24×7
₹36,700Buy Now →+GST · Monthly billing≈ ₹63/hr on demand
For single users & PoC · 1 GPU
1×
L4GPU Cloud Standard
Server Type
Dedicated GPU VM
GPU
1 × 24 GB
Virtual CPU
16 vCPU
Memory
64 GB
NVMe Storage
500 GB
Network Port
1 Gbps
Dedicated IP
1
Operating System
Ubuntu 22.04 / Win Server 2025
Drivers
CUDA pre-installed
Protection
Virtual Firewall + Anti-DDoS
Endpoint Security
Acronis Cyber Protect Cloud
Support
24×7
₹48,200Buy Now →+GST · Monthly billing≈ ₹83/hr on demand
For teams & multi-GPU · 2 GPUs
2×
L4GPU Cloud Duo
Server Type
Dedicated GPU VM
GPU
2 × 24 GB
Virtual CPU
24 vCPU
Memory
96 GB
NVMe Storage
1000 GB
Network Port
1 Gbps
Dedicated IP
1
Operating System
Ubuntu 22.04 / Win Server 2025
Drivers
CUDA pre-installed
Protection
Virtual Firewall + Anti-DDoS
Endpoint Security
Acronis Cyber Protect Cloud
Support
24×7
₹84,900Buy Now →+GST · Monthly billing≈ ₹145/hr on demand
For teams & multi-GPU · 2 GPUs
2×
L4GPU Cloud Duo Max
Server Type
Dedicated GPU VM
GPU
2 × 24 GB
Virtual CPU
32 vCPU
Memory
128 GB
NVMe Storage
1000 GB
Network Port
1 Gbps
Dedicated IP
1
Operating System
Ubuntu 22.04 / Win Server 2025
Drivers
CUDA pre-installed
Protection
Virtual Firewall + Anti-DDoS
Endpoint Security
Acronis Cyber Protect Cloud
Support
24×7
₹96,300Buy Now →+GST · Monthly billing≈ ₹165/hr on demand
For training & render farms · 4 GPUs
4×
L4GPU Cloud Quad
Server Type
Dedicated GPU VM
GPU
4 × 24 GB
Virtual CPU
48 vCPU
Memory
192 GB
NVMe Storage
2000 GB
Network Port
1 Gbps
Dedicated IP
1
Operating System
Ubuntu 22.04 / Win Server 2025
Drivers
CUDA pre-installed
Protection
Virtual Firewall + Anti-DDoS
Endpoint Security
Acronis Cyber Protect Cloud
Support
24×7
₹1,69,700Buy Now →+GST · Monthly billing≈ ₹291/hr on demand
Indicative pricing in INR, exclusive of 18% GST. Plan codes: XG.L4.1-8, XG.L4.1-16, XG.L4.2-24, XG.L4.2-32, XG.L4.4-48.
Hourly Or Monthly? Work It Out.
Tell us how much you'll actually use the GPU and we'll show the cheaper way to pay.
Pay-as-you-go—
Monthly plan—
1-year plan (per month)—
—
Indicative, excl. GST.
KEY FEATURES OF L4 On XCELLHOST
Performance per watt72 W per card means more inference per rack and per rupee — ideal for always-on services.
FP8 for modern inferenceFourth-generation Tensor Cores with FP8 run quantised LLMs, RAG and diffusion models efficiently.
AV1 video at densityDedicated NVENC/NVDEC engines with AV1 handle live transcoding, streaming and video AI pipelines.
Scales out, not upSmall, efficient instances you can add one at a time behind Kubernetes or a load balancer.
India-hosted, low latencyServe users across India from Indian data centres, with data residency for DPDP Act comfort.
Live GPU monitoringPer-GPU utilisation, memory and encoder/decoder load with alerting.
Hourly or term billingProve the workload by the hour, then save up to 10% on a 1-year term.
Experts on callWe help with TensorRT, Triton, DeepStream and FFmpeg tuning for your streams and models.
WHY CHOOSE XCELLHOST FOR YOUR L4 CLOUD GPU
Hosted In India
GPUs run in Indian data centres, so latency stays low and your data stays in the country for DPDP Act comfort.
INR Billing With GST Invoice
Pay in rupees and claim input tax credit — no forex swings or USD card charges.
99.95% Uptime SLA
Enterprise power, cooling and network with a written uptime commitment.
24×7 Human GPU Experts
Real engineers on phone, WhatsApp and ticket — in English and Hindi.
Free Setup & Migration
We install drivers, CUDA and frameworks, and move your data and images for you.
Scale 1 → 4 GPUs
Start with one GPU for a proof of concept and add more as projects grow.
ISO 27001 Security
Certified operations, virtual firewall, anti-DDoS and Acronis endpoint protection.
No Surprise Bills
Flat plans include storage, a public IP and bandwidth — no hidden egress charges.
OUTCOMES YOU CAN PLAN AROUND
3.7×
FP16 Tensor Vs T4
242 versus 65 TFLOPS for modern inference.
1.5×
Memory Vs T4
24 GB against 16 GB for larger models and batches.
97%
Of A10 Compute
Near-A10 throughput at 72 W instead of 150 W.
₹0
Hardware Capex
Add capacity one instance at a time, billed monthly.
Ratios use NVIDIA's published specifications. Actual results depend on your model, precision and batch size.
WHAT ARE THE NVIDIA L4 SPECIFICATIONS?
1
24 GB ECC Memory
24 GB GDDR6 — enough for quantised 7B–13B LLMs, many concurrent requests and high-resolution video streams.
2
7,424 CUDA · 240 Tensor Cores
Fourth-generation Tensor Cores with FP8 — up to 485 TFLOPS for quantised inference in 72 W.
3
AV1 Media Engines
Two NVENC and four NVDEC engines with AV1 support for dense, efficient video transcoding and streaming.
4
PCIe Gen 4 X16
Single-slot, low-profile card — dense servers with many GPUs per node.
Architecture
NVIDIA Ada Lovelace
GPU memory
24 GB GDDR6
Memory bandwidth
300 GB/s
CUDA cores
7,424
Tensor cores
240 (4th gen)
RT cores
60 (3rd gen)
FP8 Tensor
485 TFLOPS*
FP16/BF16 Tensor
242 TFLOPS*
TF32 Tensor
120 TFLOPS*
FP32
30.3 TFLOPS
Media engines
2 NVENC · 4 NVDEC · 4 JPEG (AV1)
Interconnect
PCIe Gen 4 x16
Form factor
Single-slot, low-profile
Board power
72 W
*With sparsity, per NVIDIA's published L4 specifications.
PERFORMANCE
L4 against earlier inference GPUs — published specifications, side by side.
GPU Workstation On-Premises VS L4 On Cloud
Buying your own workstation
XcellHost GPU Cloud
₹8–10 lakh+ upfront hardware capex
Monthly OPEX from ₹36,700 — no capex
Hardware ages out in about three years
Move to newer GPUs whenever you're ready
Power, cooling and UPS are your problem
Tier-IV class data-centre power and cooling
Usable only at the office desk
Access from office, home or site, on any device
Manual backups, if any
Snapshot and Acronis backup options
Needs in-house IT to maintain
Managed 24×7 by certified experts
One faulty part stops all work
Hardware replacement backed by an SLA
Fixed capacity, idle most nights
Scale up for deadlines, down when done
Launch L4 In The Cloud 4 Easy Steps
01
Share Your Workload
Tell us the model, scene or software you'll run and your hours of use. We reply with a sizing note and a GST-ready quote.
02
Pick A Plan And Term
Choose hourly for a proof of concept, or a monthly to 1-year L4 plan. KYC and a PO are all we need.
03
We Deliver Your GPU Server
We provision the L4 with your OS, drivers, CUDA and frameworks, then share SSH or remote-desktop access.
04
Run, Monitor And Scale
Track GPU use from the portal, call 24×7 support any time, and add GPUs as projects grow.
What is the NVIDIA L4 GPU and when should I use it?
The NVIDIA L4 is a 72 W Ada Lovelace GPU with 24 GB of GDDR6, FP8 Tensor Cores and AV1 media engines, built for efficient AI inference, video processing and edge workloads. Choose it for always-on inference and video services; choose L40S or A100/H100 for heavier generative AI or training. XcellHost rents it in India from ₹36,700 a month (excl. GST).
When should I choose L4 instead of L40S or A100?
Choose L4 for efficient inference, video and edge workloads. Choose L40S for heavier generative AI and graphics, and A100, H100 or H200 for large-scale training. You can mix GPU types at XcellHost as workloads change.
Is the L4 good for LLMs?
Yes, for inference. With FP8 or 4-bit quantisation it serves 7B–13B models for chatbots and RAG efficiently. It isn't designed for large training runs.
Does it support AV1?
Yes. Two NVENC and four NVDEC engines support AV1, H.264 and H.265 encode and decode, plus JPEG decoders — suited to live transcoding, conferencing and video AI pipelines.
How does L4 reduce GPU costs?
At 72 W it delivers high performance per watt, so each server handles more requests or streams. That means fewer servers and a lower monthly GPU bill than oversized GPUs or CPU-only inference.
Is it suitable for edge and low-latency deployments?
Yes. Its low-profile, low-power design suits edge servers, and hosting in Indian data centres keeps latency low for users in India.
Can I run it with Docker and Kubernetes?
Yes — it's container-ready and works with the NVIDIA GPU Operator on Kubernetes for autoscaled inference.
What does the L4 cost in India?
From ₹36,700 per month for one L4 with 8 vCPU and 32 GB RAM, excluding GST. 3-, 6- and 12-month terms save 5%, 7.5% and 10%.
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