Specifications Compared
| Spec | L4 | Quadro RTX 5000 |
|---|---|---|
| TDP | 72W | 230W |
| VRAM | 24 GB | 16 GB |
| CUDA Cores | 7,424 | 3,072 |
| FP8 (dense) | 242 TFLOPS | Not published |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Ada Lovelace | Turing |
| FP16 (dense) | 121 TFLOPS | 89.2 TFLOPS |
| Form Factors | PCIe | PCIe |
| INT8 (dense) | 242 TOPS | 178.4 TOPS |
| Interconnect | PCIe 4.0 | NVLink, PCIe 3.0 |
| Tensor Cores | 232 | 384 |
| FP32 Performance | 30.3 TFLOPS | 11.2 TFLOPS |
| FP64 Performance | 0.5 TFLOPS | Not published |
| Memory Bandwidth | 300 GB/s | 448 GB/s |
| FP8 (with sparsity) | 485 TFLOPS | Not published |
| FP16 (with sparsity) | 242 TFLOPS | Not published |
| INT8 (with sparsity) | 485 TOPS | Not published |
Performance Analysis
FP16 dense performance reaches 121 TFLOPS on the L4 compared with 89.2 TFLOPS on the Quadro RTX 5000. This delta indicates the L4 can complete matrix operations in training and inference workloads at a higher rate when sparsity remains disabled. FP32 figures of 30.3 TFLOPS versus 11.2 TFLOPS further widen the gap for single precision scientific kernels. Memory bandwidth of 300 GB/s on the L4 versus 448 GB/s on the Quadro RTX 5000 limits maximum batch sizes more on the L4 during memory intensive inference passes. FP16 with sparsity reaches 242 TFLOPS on the L4 while the Quadro RTX 5000 publishes no equivalent sparsity figure. INT8 dense performance lists 242 TOPS on the L4 against 178.4 TOPS on the Quadro RTX 5000.
Current On-Demand Offers
Cheapest secure on-demand offer per provider that is reported in stock right now, per GPU per hour; multi-GPU instances show the whole-instance price alongside. Deploy opens the DeployGPU console for providers on the platform, otherwise the provider's own site. Stock is rechecked every minute.
L4
| Provider | Region | GPUs | Per GPU / hr | Instance / hr | Deploy |
|---|---|---|---|---|---|
| RunPod | global | 1 | $0.59 | — | Deploy |
| Scaleway | Warsaw, Poland (WAW2) | 2 | $0.89 | $1.77 | Deploy |
2 providers in stock, 4 offers (cheapest per provider shown). All L4 offers, price history and alerts
Quadro RTX 5000
| Provider | Region | GPUs | Per GPU / hr | Instance / hr | Deploy |
|---|---|---|---|---|---|
| Paperspace | ny2 | 2 | $0.82 | $1.64 | Deploy |
1 provider in stock, 2 offers (cheapest per provider shown). All Quadro RTX 5000 offers, price history and alerts
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When to Choose the L4
The L4 suits deployments where power limits constrain rack density because its TDP measures 72W. Inference pipelines that require FP8 dense performance at 242 TFLOPS also align with the L4 specification.
When to Choose the Quadro RTX 5000
The Quadro RTX 5000 fits applications that require 448 GB/s memory bandwidth to sustain larger batch transfers. NVLink interconnect availability on the Quadro RTX 5000 enables multi GPU scaling not listed for the L4. Older Turing based code paths that already target 16 GB GDDR6 configurations continue without migration on the Quadro RTX 5000.
Use Cases
The L4 supplies 121 TFLOPS FP16 dense and 24 GB GDDR6 VRAM for larger model partitions.
FP8 dense performance of 242 TFLOPS on the L4 accelerates quantized inference relative to the Quadro RTX 5000.
Higher FP32 at 30.3 TFLOPS and lower 72W TDP on the L4 reduce energy cost during parameter updates.
Memory bandwidth of 448 GB/s on the Quadro RTX 5000 supports larger image batches than the 300 GB/s on the L4.
FP32 throughput of 30.3 TFLOPS on the L4 exceeds the 11.2 TFLOPS rating of the Quadro RTX 5000.
Frequently Asked Questions
What are the FP16 dense ratings?▾
The L4 lists 121 TFLOPS FP16 dense and the Quadro RTX 5000 lists 89.2 TFLOPS FP16 dense.
Which GPU has lower power draw?▾
The L4 TDP measures 72W while the Quadro RTX 5000 TDP measures 230W.
Does the L4 support sparsity in FP16?▾
The L4 publishes FP16 with sparsity at 242 TFLOPS while the Quadro RTX 5000 publishes no sparsity figure.
How do FP32 numbers compare?▾
The L4 reaches 30.3 TFLOPS FP32 and the Quadro RTX 5000 reaches 11.2 TFLOPS FP32.
Which is cheaper to rent, the L4 or the Quadro RTX 5000?▾
Cloud rental prices for both the L4 and Quadro RTX 5000 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 L4 have compared to the Quadro RTX 5000?▾
The L4 has 24 GB of GDDR6 memory. The Quadro RTX 5000 has 16 GB of GDDR6 memory.
Can I find L4 and Quadro RTX 5000 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 L4 and the Quadro RTX 5000?▾
The L4 uses the Ada Lovelace architecture (2023) while the Quadro RTX 5000 uses Turing (2018). The L4 delivers 1.4x the dense FP16 throughput (121 vs 89.2 TFLOPS, both without sparsity) while the Quadro RTX 5000 has 1.5x the memory bandwidth of the L4.
Rent these GPUs
Each GPU page lists every current on-demand offer by provider, per GPU-hour, updated every minute.
Related comparisons
How this page is made
- Specifications come from the NVIDIA, AMD and Intel datasheets for the L4 and the Quadro RTX 5000. Dense and sparse throughput are listed separately.
- Prices and availability are live: every offer shown is an in-stock, on-demand listing from a provider we track, rechecked every minute.
- The written comparison (overview, performance notes, when to choose each card, verdict, use cases and FAQ) was drafted with an AI model from the specification table above and passed an automated check that rejects any figure not in that table. It was last generated on . It contains no prices; those are always read live.
- Read how we collect the data, or report an error on this page.
Next steps
- Rent L4Every current offer by provider, daily price history and a price alert.
- Rent QUADRO RTX 5000Every current offer by provider, daily price history and a price alert.
- GPU price indexHow on-demand prices for the major GPUs have moved, updated daily.
- All GPUsEvery GPU we track, with current lows and provider counts.