Specifications Compared
| Spec | L4 | P100 |
|---|---|---|
| TDP | 72W | 250W |
| VRAM | 24 GB | 16 GB |
| CUDA Cores | 7,424 | 3,584 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Ada Lovelace | Pascal |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | PCIe 4.0 | NVLink |
| Tensor Cores | 232 | |
| FP8 Performance | 242 TFLOPS | |
| FP16 Performance | 121 TFLOPS | 9.3 TFLOPS |
| FP32 Performance | 30.3 TFLOPS | 9.3 TFLOPS |
| FP64 Performance | 0.5 TFLOPS | 4.7 TFLOPS |
| INT8 Performance | 242 TOPS | |
| Memory Bandwidth | 300 GB/s | 732 GB/s |
Performance Analysis
Compute performance favors the L4 decisively: it delivers 121 TFLOPS in FP16 and 30.3 TFLOPS in FP32, surpassing the P100's 9.3 TFLOPS in both formats by over 13 times in FP16. This disparity accelerates deep learning training and inference, where FP16 dominates modern workflows for LLMs and vision models, reducing computation time significantly.
Memory specs shape real-world usage: the L4's 24 GB VRAM supports larger models or batch sizes than the P100's 16 GB, preventing out-of-memory errors in inference pipelines. Although the P100's 732 GB/s bandwidth exceeds the L4's 300 GB/s, enabling larger effective batch sizes in memory-bound operations, the L4's FP8 capability at 242 TFLOPS optimizes quantized inference. Lower 72W TDP on the L4 enhances density in cloud racks, unlike the power-hungry 250W P100.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
L4
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA L4 24GB VRAM | 24GB | 64 vCPU 101GB RAM 485GB Storage | Iceland | $0.33/GPU/hr | Available | ||
 RunPod | NVIDIA L4 24GB VRAM | 24GB | 12 vCPU 50GB RAM | 🌍global | $0.39/GPU/hr | |||
 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 |
P100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 LeaderGPU | 2×NVIDIA Tesla P100 16GB VRAM | 16GB | 0 vCPU 256GB RAM 960GB Storage | Netherlands | $0.60/GPU/hr $1.20/hr total (2×) | Available |
When to Choose the L4
The L4 stands out for modern AI workloads: its 121 TFLOPS FP16 and 242 TFLOPS FP8 enable rapid LLM inference and fine-tuning, while 24 GB VRAM accommodates models exceeding 16 GB. Low 72W TDP and PCIe 4.0 interconnect suit power-constrained, high-density cloud deployments at $0.32 per hour starting price.
Inference-heavy applications benefit most, as Ada Lovelace optimizations outperform Pascal in half-precision tasks common today.
When to Choose the P100
The P100 fits extreme budget constraints: at $0.07 per hour, it delivers 9.3 TFLOPS FP32 and 732 GB/s bandwidth for legacy HPC or scientific simulations where high throughput trumps raw compute. NVLink interconnect aids multi-GPU setups unavailable on the L4.
It serves transitional workloads on older Pascal-optimized code, avoiding migration costs despite 250W power draw.
Use Cases
L4's 121 TFLOPS FP16 and 30.3 TFLOPS FP32 vastly outpace P100's 9.3 TFLOPS, accelerating large model training. Additional 24 GB VRAM supports bigger batches than 16 GB.
L4's 242 TFLOPS FP8 and 121 TFLOPS FP16 optimize quantized serving, far exceeding P100 capabilities. 24 GB VRAM handles production-scale models.
Superior 30.3 TFLOPS FP32 on L4 speeds parameter updates over P100's 9.3 TFLOPS. More VRAM enables larger datasets.
Ada architecture and 121 TFLOPS FP16 on L4 boost image generation speed versus Pascal's limits. 24 GB fits complex diffusion models.
P100's 732 GB/s bandwidth and NVLink excel in memory-intensive simulations over L4's 300 GB/s. Lower $0.07 per hour cost suits bulk compute.
Frequently Asked Questions
Which GPU has more VRAM, L4 or P100?▾
The L4 provides 24 GB GDDR6 VRAM, exceeding the P100's 16 GB HBM2. This allows the L4 to load larger AI models without swapping. Capacity difference aids modern inference tasks.
How do L4 and P100 compare in FP16 performance?▾
L4 achieves 121 TFLOPS FP16, over 13 times the P100's 9.3 TFLOPS. This boosts training and inference speeds in half-precision ML workflows. P100 lags in contemporary deep learning.
What are the cloud pricing differences for L4 vs P100?▾
L4 starts at $0.32 per hour averaging $0.68 across 15 offers, while P100 begins at $0.07 per hour averaging $0.25 across 3. P100 offers better value for legacy use. Prices reflect real-time gpuperhour.com data.
Which has higher memory bandwidth?▾
P100 delivers 732 GB/s with HBM2, surpassing L4's 300 GB/s GDDR6. High bandwidth on P100 benefits large-batch or bandwidth-bound computations. L4 compensates with more VRAM.
L4 vs P100 power consumption?▾
L4 uses 72W TDP, far lower than P100's 250W. This enables denser cloud deployments for L4. Power efficiency favors L4 in cost-sensitive racks.
Is L4 or P100 better for AI inference?▾
L4 excels with 242 TFLOPS FP8 and 121 TFLOPS FP16 versus P100's lacks. 24 GB VRAM supports production LLMs. Modern architecture makes L4 preferable.
Which is cheaper to rent, the L4 or the P100?▾
Cloud rental prices for both the L4 and P100 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 P100?▾
The L4 has 24 GB of GDDR6 memory. The P100 has 16 GB of HBM2 memory.
Can I find L4 and P100 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 P100?▾
The L4 uses the Ada Lovelace architecture (2023) while the P100 uses Pascal (2016). The L4 delivers 13.0x the FP16 throughput and 2.4x the memory bandwidth of the P100.