Specifications Compared
| Spec | L40 | RTX-4080 |
|---|---|---|
| TDP | 300W | 320W |
| VRAM | 48 GB | 16 GB |
| CUDA Cores | 18,176 | 9,728 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ada Lovelace | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 568 | 304 |
| FP16 Performance | 90.5 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 90.5 TFLOPS | 48.7 TFLOPS |
| INT8 Performance | 724 TOPS | 780 TOPS |
| Memory Bandwidth | 864 GB/s | 717 GB/s |
Performance Analysis
Superior compute defines the L40's edge: 90.5 TFLOPS in FP16 and FP32 supports twice the throughput of the RTX 4080 SUPER's 48.7 TFLOPS, accelerating neural network training and inference in AI pipelines. Equal tensor-to-scalar ratios in both GPUs preserve performance across precisions, but the L40's higher peaks translate to faster epochs in model training.
Memory specifications favor the L40 profoundly: 48 GB GDDR6 versus 16 GB GDDR6X enables handling models like 70B parameter LLMs without quantization, while 864 GB/s bandwidth exceeds 717 GB/s to minimize stalls in data loading. Larger batch sizes become viable on the L40, reducing per-sample overhead in inference servers and improving utilization in training runs.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
L40
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA L40S 48GB VRAM | 48GB | 0 vCPU 0GB RAM | Wolverhampton | $0.55/GPU/hr | Available | ||
 RunPod | NVIDIA L40 48GB VRAM | 48GB | 8 vCPU 94GB RAM | 🌍global | $0.82/GPU/hr | |||
RunPod | NVIDIA L40S 48GB VRAM | 48GB | 16 vCPU 94GB RAM | 🌍global | $0.86/GPU/hr | |||
 Massed Compute | NVIDIA L40 48GB VRAM | 48GB | 14 vCPU 72GB RAM 625GB Storage | Iowa | $0.86/GPU/hr | Available | ||
Massed Compute | 2×NVIDIA L40 48GB VRAM | 48GB | 26 vCPU 144GB RAM 1250GB Storage | Iowa | $0.86/GPU/hr $1.72/hr total (2×) | Available |
RTX 4080 SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
RunPod | NVIDIA GeForce RTX 4080 SUPER 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr | |||
RunPod | NVIDIA GeForce RTX 4080 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the L40
Select the L40 for memory-bound workloads such as training or inferring large language models exceeding 16 GB VRAM. Its 48 GB capacity and 864 GB/s bandwidth sustain high batch sizes, paired with 90.5 TFLOPS for production-scale throughput. Datacenter deployments benefit from this combination over consumer alternatives.
When to Choose the RTX 4080 SUPER
The RTX 4080 SUPER suits cost-sensitive prototyping and smaller-scale AI tasks fitting within 16 GB VRAM. At $0.17 per hour average $0.32, it delivers 48.7 TFLOPS efficiently for fine-tuning or inference on models under 7B parameters. Gaming or visual effects workloads leverage its GDDR6X memory effectively.
Use Cases
L40's 48 GB VRAM supports massive models without offloading; 90.5 TFLOPS halves training time versus 48.7 TFLOPS on RTX 4080 SUPER.
Higher 864 GB/s bandwidth and 48 GB VRAM enable larger batches for low-latency serving; outperforms RTX 4080 SUPER's 16 GB limit.
RTX 4080 SUPER suffices for models under 16 GB at lower $0.32 per hour cost; L40 excels if datasets demand more VRAM.
16 GB GDDR6X handles image generation pipelines efficiently at 48.7 TFLOPS; $0.17 per hour pricing fits iterative creative workflows.
90.5 TFLOPS FP32 and 864 GB/s bandwidth accelerate simulations; 48 GB VRAM processes large datasets without bottlenecks.
Frequently Asked Questions
Which GPU has more VRAM: L40 or RTX 4080 SUPER?▾
The L40 provides 48 GB GDDR6 VRAM, three times the RTX 4080 SUPER's 16 GB GDDR6X. This advantage suits large AI models. Cloud pricing reflects capacity: L40 averages $0.89 per hour.
How do FP16 performance levels compare between L40 and RTX 4080 SUPER?▾
L40 achieves 90.5 TFLOPS FP16, nearly double the RTX 4080 SUPER's 48.7 TFLOPS. Faster AI training results from this gap. Inference speeds scale similarly.
What is the memory bandwidth difference for L40 versus RTX 4080 SUPER?▾
L40 offers 864 GB/s, surpassing RTX 4080 SUPER's 717 GB/s by 20 percent. Larger batches avoid bottlenecks in training. This impacts data-heavy workloads.
Which GPU is cheaper in the cloud: L40 or RTX 4080 SUPER?▾
RTX 4080 SUPER starts at $0.17 per hour averaging $0.32, far below L40's $0.67 minimum and $0.89 average. Budget tasks favor the SUPER. Performance per dollar varies by use.
Do L40 and RTX 4080 SUPER have the same TDP?▾
L40 consumes 300W TDP, slightly under RTX 4080 SUPER's 320W. Both fit PCIe slots efficiently. Power efficiency aligns with Ada Lovelace design.
Can RTX 4080 SUPER handle large LLMs compared to L40?▾
RTX 4080 SUPER's 16 GB VRAM limits it to smaller models under 13B parameters without heavy quantization. L40's 48 GB manages 70B comfortably. Choose based on model size.
Which is cheaper to rent, the L40 or the RTX 4080?▾
Cloud rental prices for both the L40 and RTX 4080 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the L40 have compared to the RTX 4080?▾
The L40 has 48 GB of GDDR6 memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find L40 and RTX 4080 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the L40 and the RTX 4080?▾
The L40 uses the Ada Lovelace architecture (2023) while the RTX 4080 uses Ada Lovelace (2022). The L40 delivers 1.9x the FP16 throughput and 1.2x the memory bandwidth of the RTX 4080.