Handle demanding AI inference workloads with efficient 72 W NVIDIA L4 GPUs, reducing infrastructure costs while maintaining reliable performance.
Launch Time
vGPU Instances
Virtualization
Lower Cost
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Architecture
GPU Memory
Memory Bandwidth
FP8 Tensor
FP16 Tensor
FP32 Performance
Interconnect
PCIe Gen4 x16
Same NVIDIA GPUs, lower spend, India-first regions and 24/7 human support.
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What Matters
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BTrack
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Hyperscalers
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GPU Pricing
Cost structure
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Monthly plans with up to 60% savings. | Higher long-term flat yearly rate. |
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Billing & Egress
Transparency
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Simple bill with predictable egress. | Many line items and surprise charges. |
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Data Location
Regional presence
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India-first GPU regions, low latency. | Fewer India GPU options, higher latency/cost. |
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GPU Availability
Access to capacity
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Capacity planned around AI clusters. | Popular GPUs often quota-limited. |
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Support
Help when you need it
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24/7 human GPU specialists. | Tiered, ticket-driven support; faster help extra. |
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Commitment & Flexibility
Scaling options
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Start with one GPU, scale up. | Best deals need big upfront commits. |
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Open-source & Tools
Ready-to-use models
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Ready-to-run open-source models, standard stack. | More DIY setup around base GPUs. |
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Migration & Onboarding
Getting started
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Guided migration and DR planning. | Mostly self-serve or paid consulting. |
Run AI models, NLP, recommendations, and GenAI applications efficiently.
Accelerate image analysis, object detection, and real-time visual processing.
Handle video encoding, decoding, analytics, and streaming workloads with ease.
Deliver high-quality video content with fast and efficient GPU acceleration.
Power 3D design, visualization, CAD, and other graphics-intensive applications.
Deploy GPU workloads efficiently across cloud and edge environments.
Accelerate image generation, content creation, and AI-powered creative applications.
Get an NVIDIA L4 configuration tailored to your specific workload requirements.
Talk to us to find out how we can help you achieve your IT objectives with the utmost security and peace of mind.
We stay ahead of curve, leveraging cutting-edge technologies and strategies to remain competitive. Explore our frequently asked questions below for quick guidance.
NVIDIA L4 is a low-power GPU based on the Ada Lovelace architecture, designed for AI inference, video processing, graphics, virtual workstations, and other data-center workloads.
NVIDIA L4 features 24GB GDDR6 memory, approximately 300GB/s memory bandwidth, and a 72W power envelope, making it suitable for efficient AI and accelerated computing deployments.
Yes. NVIDIA L4 can handle AI inference, smaller and optimized LLM deployments, Transformer models, recommendation systems, and generative AI applications where power efficiency and cost control are important.
NVIDIA L4 is well suited for AI inference, video transcoding, intelligent video analytics, graphics rendering, virtual desktops, content delivery, and other workloads requiring efficient GPU acceleration.
Its 72W power consumption and compact form factor allow organizations to deploy more GPU resources within limited power and server capacity, helping reduce infrastructure and operational costs.
NVIDIA L4 focuses on power-efficient inference, media, and general-purpose acceleration, while A100 targets large-scale AI and HPC workloads and L40S provides higher performance for demanding AI, graphics, and visualization workloads.
Yes. Btrack India provides NVIDIA L4 GPU infrastructure for businesses and developers that need scalable GPU resources for AI inference, video processing, graphics, and other accelerated workloads.
Yes. NVIDIA L4 is designed for data-center deployments and can support enterprise AI inference, video applications, virtual workstations, and other production workloads requiring reliable and power-efficient GPU acceleration.
