Specifications Compared
| Spec | L4 | RTX-3090 |
|---|---|---|
| TDP | 72W | 350W |
| VRAM | 24 GB | 24 GB |
| CUDA Cores | 7,424 | 10,496 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ada Lovelace | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | PCIe 4.0 | NVLink |
| Tensor Cores | 232 | 328 |
| FP8 Performance | 242 TFLOPS | |
| FP16 Performance | 121 TFLOPS | 35.6 TFLOPS |
| FP32 Performance | 30.3 TFLOPS | 35.6 TFLOPS |
| FP64 Performance | 0.5 TFLOPS | |
| INT8 Performance | 242 TOPS | |
| Memory Bandwidth | 300 GB/s | 936 GB/s |
Performance Analysis
FP16 performance defines a clear winner for modern AI: L4 achieves 121 TFLOPS, over 3x the RTX 3090's 35.6 TFLOPS, accelerating mixed-precision training and inference where tensor cores dominate. L4's exclusive FP8 at 242 TFLOPS supports quantized models, slashing inference latency for LLMs without accuracy loss.
FP32 parity is close, with RTX 3090 at 35.6 TFLOPS slightly above L4's 30.3 TFLOPS, suiting graphics or simulations reliant on single-precision math. Bandwidth gap is stark: RTX 3090's 936 GB/s GDDR6X versus L4's 300 GB/s GDDR6 permits larger batch sizes in training, reducing I/O bottlenecks and improving throughput for data-heavy workloads.
Power disparity underscores efficiency: L4's 72W TDP delivers high TFLOPS per watt, ideal for sustained cloud runs, while RTX 3090's 350W demands robust cooling, limiting scalability in multi-GPU setups.
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 |
RTX 3090
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
TensorDock | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 0 vCPU 0GB RAM | Wilmington, Delaware | $0.20/GPU/hr | Available | ||
TensorDock | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 0 vCPU 0GB RAM | Dallas, Texas | $0.21/GPU/hr | Available | ||
Vast.ai | 4×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 32 vCPU 403GB RAM 104GB Storage | Iceland | $0.25/GPU/hr $1.01/hr total (4×) | Available | ||
Vast.ai | 4×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 32 vCPU 252GB RAM 1217GB Storage | Finland | $0.27/GPU/hr $1.07/hr total (4×) | Available | ||
 LeaderGPU | 8×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.29/GPU/hr $2.29/hr total (8×) | Available |
When to Choose the L4
The L4 stands out for inference-dominated pipelines and power-constrained environments. Its 121 TFLOPS FP16 and 242 TFLOPS FP8 enable rapid LLM serving with low latency, perfect for edge or dense cloud deployments at 72W TDP. PCIe 4.0 ensures reliable datacenter integration without NVLink complexity.
When to Choose the RTX 3090
Opt for RTX 3090 in bandwidth-intensive training or budget setups. The 936 GB/s memory bandwidth supports massive batches for fine-tuning, complemented by NVLink for multi-GPU scaling. At $0.08/hr starting price, it offers strong FP32 at 35.6 TFLOPS for cost-sensitive scientific tasks.
Use Cases
RTX 3090's 936 GB/s bandwidth enables larger batch sizes essential for efficient training. Its 35.6 TFLOPS FP32 handles the precision needs effectively.
L4's 121 TFLOPS FP16 and 242 TFLOPS FP8 accelerate quantized serving with minimal latency. Low 72W TDP suits high-density deployments.
High 936 GB/s bandwidth supports data-heavy fine-tuning batches. Lower $0.08/hr pricing maximizes experimentation value.
L4's superior 121 TFLOPS FP16 speeds image generation inference. FP8 capability optimizes throughput for generative tasks.
RTX 3090's 35.6 TFLOPS FP32 and 936 GB/s bandwidth excel in simulations. NVLink aids multi-GPU parallelism.
Frequently Asked Questions
What is the VRAM difference between L4 and RTX 3090?▾
Both GPUs feature 24 GB of VRAM, with L4 using GDDR6 and RTX 3090 using GDDR6X. This equality suits memory-intensive AI models equally.
Which has higher power consumption?▾
RTX 3090 consumes 350W TDP, compared to L4's 72W. L4 enables more efficient, cooler deployments.
How do cloud prices compare?▾
L4 starts at $0.32/hr with $0.68/hr average across 15 offers. RTX 3090 starts at $0.08/hr with $0.43/hr average across 48 offers.
Is L4 faster for AI inference?▾
Yes, L4 delivers 121 TFLOPS FP16 and 242 TFLOPS FP8, versus RTX 3090's 35.6 TFLOPS FP16. This boosts quantized LLM serving.
What architectures do they use?▾
L4 uses Ada Lovelace from 2023, RTX 3090 uses Ampere from 2020. Ada provides advanced tensor cores for modern workloads.
Which supports multi-GPU better?▾
RTX 3090 uses NVLink for high-speed interconnects. L4 relies on PCIe 4.0, sufficient for single-node tasks.
Which is cheaper to rent, the L4 or the RTX 3090?▾
Cloud rental prices for both the L4 and RTX 3090 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 RTX 3090?▾
The L4 has 24 GB of GDDR6 memory. The RTX 3090 has 24 GB of GDDR6X memory.
Can I find L4 and RTX 3090 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 RTX 3090?▾
The L4 uses the Ada Lovelace architecture (2023) while the RTX 3090 uses Ampere (2020). The L4 delivers 3.4x the FP16 throughput and 3.1x the memory bandwidth of the RTX 3090.