NVIDIA L4 Cloud GPU
Compare NVIDIA L4 specifications, AI inference, video and graphics capabilities before choosing a cloud GPU provider.
NVIDIA Ada Lovelace universal accelerator
Efficient acceleration for AI, video and graphics
NVIDIA L4 is a low-profile data-center GPU designed for efficient AI inference, video processing, virtual desktops and graphics. Its 24 GB memory, 72 W power envelope and dedicated media engines make it suitable for dense cloud, enterprise and edge deployments.
- Ada LovelaceGPU architecture
- 24 GBGPU memory
- 300 GB/sMemory bandwidth
- 72 WMaximum TDP
Who should choose an L4 cloud GPU?
Choose L4 for efficient mainstream inference, video AI, streaming, virtual desktops or graphics workloads that fit within 24 GB. Consider a higher-memory GPU when the model, KV cache, batch size or training workload exceeds that capacity.
NVIDIA L4 specifications
L4 combines low power consumption and a compact server form factor with fourth-generation Tensor Cores and dedicated video acceleration.
| Specification | NVIDIA L4 |
|---|---|
| Architecture | NVIDIA Ada Lovelace |
| GPU memory | 24 GB |
| Memory bandwidth | 300 GB/s |
| FP32 | 30.3 TFLOPS |
| TF32 Tensor Core* | 120 TFLOPS |
| FP16 Tensor Core* | 242 TFLOPS |
| BF16 Tensor Core* | 242 TFLOPS |
| FP8 Tensor Core* | 485 TFLOPS |
| INT8 Tensor Core* | 485 TOPS |
| NVENC / NVDEC / JPEG | 2 / 4 / 4 |
| Interconnect | PCIe Gen4 x16, 64 GB/s |
| Form factor | Single-slot, low-profile PCIe |
| Maximum TDP | 72 W |
| Supported server configurations | Partner and NVIDIA-Certified Systems with 1–8 GPUs |
* NVIDIA publishes Tensor Core figures with sparsity enabled and states that performance is one-half without sparsity. The supplied datasheet does not specify MIG or NVLink support, so confirm those requirements directly with the provider or current NVIDIA documentation.
L4 advantage
Choose L4 for efficient, dense deployments
The 72 W power envelope and low-profile, single-slot design make L4 practical for servers that need several accelerators without the cooling and power requirements of higher-end data-center GPUs.
Capacity consideration
Check whether 24 GB is enough
L4 is strongest when efficiency is more important than maximum memory. Large models, long contexts and larger fine-tuning batches may require a 48 GB, 80 GB or higher-memory GPU.
What makes L4 useful?
Open each capability for a practical explanation of its role in cloud AI, video and graphics workloads.
Fourth-generation Tensor CoresFP8 acceleration for efficient AI inference
The Ada Lovelace Tensor Cores support FP8 and structured sparsity. NVIDIA positions L4 for generative AI, natural-language processing, computer vision and other inference workloads.
Advanced video accelerationTwo encoders and four decoders
L4 includes two NVENC engines, four NVDEC engines and four JPEG decoders. NVIDIA highlights AV1 support for video transcoding, streaming, conferencing and vision AI.
Third-generation RT CoresAccelerated ray tracing and neural graphics
Third-generation RT Cores improve ray-tracing throughput for real-time rendering, cloud gaming, virtual worlds and graphics-based enterprise workloads.
DLSS 3 supportAI-assisted graphics performance
DLSS 3 uses fourth-generation Tensor Cores and the Optical Flow Accelerator to generate additional high-quality frames in supported graphics workloads.
Virtualization-readySupports NVIDIA vGPU software
NVIDIA positions L4 for RTX Virtual Workstation and Virtual PC deployments, supporting virtualized design, productivity and graphics applications.
Data-center securitySecure boot with root of trust
L4 is designed for continuous enterprise data-center operation and includes secure boot with root-of-trust technology.
Best workloads for an L4 cloud GPU
AI and generative AI inference
Optimized for inference workloads such as recommendations, generative AI, conversational assistants, visual search and contact-center automation.
Video processing and streaming
Useful for transcoding, streaming, video conferencing and AI video pipelines that benefit from dedicated AV1-capable encode and decode engines.
Computer vision and visual search
Four JPEG decoders and dedicated video engines support image-heavy and real-time vision pipelines at the cloud or edge.
Virtual workstations and graphics
Suitable for virtual desktops, RTX Virtual Workstation, cloud graphics, Omniverse and selected real-time rendering applications.
L4 is a strong fit when…
- Your model and working data fit within 24 GB of GPU memory.
- You need efficient inference rather than the highest-end training accelerator.
- You need a low-profile, single-slot GPU for dense server deployments.
- You want a 72 W accelerator for cloud, data-center or edge environments.
- Your workflow benefits from AV1 video encode and decode acceleration.
- You need one GPU for AI, video, virtual desktops and graphics.
Consider another GPU when…
L4 may not be sufficient when your workload needs more than 24 GB of memory, higher memory bandwidth or a GPU intended primarily for large-scale model training.
- Compare L40S for 48 GB memory and stronger rendering performance.
- Compare A100 for 80 GB memory, HPC and larger training workloads.
- Compare H100 or H200 for high-end transformer workloads.
Provider comparison
Cloud providers offering NVIDIA L4
Compare L4 instance resources, deployment region, starting price and billing options. Confirm whether NVENC, NVDEC, JPEG decoding, RTX or virtual GPU capabilities are exposed in the selected plan.
| Provider | L4 offering | GPU memory | Example configuration | Regions | Starting price | Billing options | Details |
|---|---|---|---|---|---|---|---|
| AceCloud | 1× NVIDIA L4 | 24 GB GDDR6 | 8 vCPU · 32 GB RAM | India and United States | From ₹36,730/month | Monthly · 6/12-month plans · selected spot | View provider |
| E2E Networks | 1× NVIDIA L4 | 24 GB GDDR6 | 25 vCPU · 110 GB RAM | India | ₹49/hour · ₹30,762/month | On-demand · monthly · 6 months · annual | View provider |
| Utho | 1× NVIDIA L4 | 24 GB GDDR6 | 8 vCPU · 32 GB RAM | India | From ₹22,995/month | On-demand · monthly · reserved capacity · spot to confirm | View provider |
| AWS | EC2 G6 | 24 GB GDDR6 per GPU | Fractional GPU to 8 GPUs · up to 192 vCPU | Selected AWS regions | Use AWS Pricing Calculator | On-Demand · Reserved Instances · Savings Plans · Spot | View provider |
Compare the complete instance rather than only the GPU price. Providers can differ in vCPU, RAM, storage, networking, region, commitment period, taxes and access to media, graphics or vGPU features. Spot capacity can be interrupted and may not be available for every L4 configuration.
NVIDIA L4 FAQs
How much GPU memory does NVIDIA L4 have?
NVIDIA L4 has 24 GB of GPU memory and 300 GB/s of memory bandwidth.
What is the maximum power consumption of NVIDIA L4?
The datasheet lists a maximum thermal design power of 72 W.
Is NVIDIA L4 suitable for LLM inference?
Yes. NVIDIA positions L4 as an efficient inference accelerator for generative AI and other mainstream AI applications, provided the model and runtime data fit within 24 GB.
Can NVIDIA L4 be used for AI training?
The datasheet says L4 can support training, inference and data science through NVIDIA AI Enterprise, but its main positioning is efficient mainstream inference, video and graphics.
How many video engines does NVIDIA L4 include?
L4 includes two NVENC encoders, four NVDEC decoders and four JPEG decoders.
What is the NVIDIA L4 form factor?
L4 is a single-slot, low-profile PCIe GPU using PCIe Gen4 x16 with 64 GB/s interconnect bandwidth.
Compare L4 configurations before choosing a provider
Compare the complete instance, not only the GPU. Check CPU, RAM, storage, networking, region, video-engine access, vGPU licensing and whether the plan is optimized for inference, video or virtual desktops.