Specifications Compared
| Spec | A100 | L4 |
|---|---|---|
| TDP | 400W | 72W |
| VRAM | 40-80 GB | 24 GB |
| CUDA Cores | 6,912 | 7,424 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | PCIe 4.0 |
| Tensor Cores | 432 | 232 |
| FP16 Performance | 312 TFLOPS | 121 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 30.3 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | 0.5 TFLOPS |
| INT8 Performance | 624 TOPS | 242 TOPS |
| Memory Bandwidth | 2,039 GB/s | 300 GB/s |
Performance Analysis
Memory specifications reveal a clear divide: the A100 SXM4 40GB holds 40 GB HBM2e with 2039 GB/s bandwidth, enabling larger batch sizes and models compared to the L4's 24 GB GDDR6 at 300 GB/s. High bandwidth on the A100 reduces data transfer bottlenecks in memory-intensive operations like transformer training, where datasets exceed 24 GB.
FP16 performance favors the A100 at 312 TFLOPS over the L4's 121 TFLOPS, accelerating mixed-precision training for deep learning models. Conversely, the L4 leads in FP32 at 30.3 TFLOPS against 19.5 TFLOPS, benefiting simulations or graphics tasks reliant on single-precision compute. The L4's FP8 capability of 242 TFLOPS enhances quantized inference efficiency.
Power differences impact scalability: the A100's 400W TDP demands robust cooling and higher costs, while the L4's 72W allows dense deployments. In real-world terms, A100 suits high-throughput training with large batches; L4 optimizes cost-sensitive inference with smaller payloads.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 SXM4 40GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 63GB RAM 2826GB Storage | Slovenia | $0.73/GPU/hr | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 794GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
 LeaderGPU | 8×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.90/GPU/hr $7.20/hr total (8×) | Available | ||
Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 63GB RAM 557GB Storage | Czechia | $1.00/GPU/hr | Available | ||
 Denvr | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 128 vCPU 1024GB RAM 15200GB Storage | Virginia | $1.15/GPU/hr $9.20/hr total (8×) |
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 |
When to Choose the A100 SXM4 40GB
Select the A100 SXM4 40GB for workloads demanding high memory capacity and bandwidth: large-scale LLM training benefits from 40 GB HBM2e and 2039 GB/s, supporting models that exceed 24 GB VRAM. Its 312 TFLOPS FP16 outperforms the L4's 121 TFLOPS, accelerating mixed-precision tasks. NVLink and InfiniBand interconnects enable multi-GPU scaling unavailable on the L4.
When to Choose the L4
Choose the L4 for power-efficient, cost-effective deployments: its 72W TDP versus 400W reduces operational expenses, ideal for dense inference servers. Superior FP32 at 30.3 TFLOPS suits scientific computing or rendering over the A100's 19.5 TFLOPS. At $0.32 per hour average $0.69 per hour, it offers value for smaller models fitting 24 GB GDDR6.
Use Cases
The A100's 40 GB HBM2e VRAM and 312 TFLOPS FP16 exceed the L4's 24 GB GDDR6 and 121 TFLOPS, enabling larger models and batches. High 2039 GB/s bandwidth minimizes bottlenecks in training.
The L4's 242 TFLOPS FP8 and 72W TDP optimize quantized inference efficiency. Lower $0.69 per hour average cost suits high-volume serving over the A100's 400W draw.
Fine-tuning benefits from A100's 40 GB VRAM for parameter-heavy models versus L4's 24 GB limit. 312 TFLOPS FP16 accelerates iterations faster than 121 TFLOPS.
Stable Diffusion fits within 24 GB VRAM on L4 for cost savings at $0.32 per hour start, but A100's bandwidth handles higher resolutions. Choice depends on scale.
L4's 30.3 TFLOPS FP32 outperforms A100's 19.5 TFLOPS for simulations. Low 72W TDP enables dense clusters without A100's power overhead.
Frequently Asked Questions
Which GPU has more VRAM, A100 or L4?▾
The A100 SXM4 40GB provides 40 GB HBM2e VRAM, surpassing the L4's 24 GB GDDR6. This advantage supports larger AI models on the A100. Bandwidth also differs at 2039 GB/s for A100 versus 300 GB/s for L4.
How do FP16 performances compare between A100 and L4?▾
A100 delivers 312 TFLOPS FP16, double the L4's 121 TFLOPS, favoring training workloads. L4 counters with 242 TFLOPS FP8 for inference. FP32 sees L4 at 30.3 TFLOPS over A100's 19.5 TFLOPS.
What are the power consumption differences?▾
The A100 requires 400W TDP, while L4 uses only 72W. This makes L4 suitable for efficient deployments. A100's higher power supports greater compute density via NVLink.
Which is cheaper in the cloud, A100 or L4?▾
L4 pricing starts at $0.32 per hour with $0.69 average across 16 offers, far below A100's $1.00 start and $2.80 average on 4 offers. L4 offers better value for light tasks.
Can L4 replace A100 for training?▾
L4 cannot fully replace A100 due to 24 GB VRAM limit versus 40 GB and lower 121 TFLOPS FP16. A100 excels for large-scale training with 2039 GB/s bandwidth.
What architectures do they use?▾
A100 uses 2020 Ampere architecture; L4 employs 2023 Ada Lovelace. Ada brings FP8 support at 242 TFLOPS on L4. Ampere provides NVLink on A100.
Which is cheaper to rent, the A100 or the L4?▾
Cloud rental prices for both the A100 and L4 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 A100 have compared to the L4?▾
The A100 has 40 to 80 GB of HBM2e memory. The L4 has 24 GB of GDDR6 memory.
Can I find A100 and L4 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 A100 and the L4?▾
The A100 uses the Ampere architecture (2020) while the L4 uses Ada Lovelace (2023). The A100 delivers 2.6x the FP16 throughput and 6.8x the memory bandwidth of the L4.