Specifications Compared
| Spec | L40 | V100 |
|---|---|---|
| TDP | 300W | 300W |
| VRAM | 48 GB | 16-32 GB |
| CUDA Cores | 18,176 | 5,120 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Ada Lovelace | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| Tensor Cores | 568 | 640 |
| FP16 Performance | 90.5 TFLOPS | 125 TFLOPS |
| FP32 Performance | 90.5 TFLOPS | 15.7 TFLOPS |
| INT8 Performance | 724 TOPS | |
| Memory Bandwidth | 864 GB/s | 900 GB/s |
Performance Analysis
FP32 performance defines a clear divide: the L40's 90.5 TFLOPS vastly exceeds the V100's 15.7 TFLOPS, accelerating single-precision training and simulation workloads where accuracy matters over speed. In contrast, V100's 125 TFLOPS FP16 outperforms L40's 90.5 TFLOPS, suiting legacy half-precision inference optimized for its tensor cores, though modern frameworks leverage mixed precision to mitigate this.
VRAM capacity impacts batch sizes directly: L40's 48 GB GDDR6 enables processing models up to three times larger than V100's 16 GB HBM2, reducing out-of-memory errors in LLM training. Memory bandwidth differences are minor, 864 GB/s versus 900 GB/s, so data transfer bottlenecks affect both similarly during high-throughput inference. The L40's balanced FP16 and FP32 profile supports versatile modern pipelines, while V100 excels in FP16-dominant legacy setups.
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 | |||
 Massed Compute | NVIDIA L40 48GB VRAM | 48GB | 14 vCPU 72GB RAM 625GB Storage | Iowa | $0.86/GPU/hr | Available | ||
RunPod | NVIDIA L40S 48GB VRAM | 48GB | 16 vCPU 94GB RAM | 🌍global | $0.86/GPU/hr | |||
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 |
Tesla V100 16GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Texas | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | New York City | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Texas | $0.29/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | New York City | $0.29/GPU/hr | Available | ||
 Lambda Labs | 8×NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 88 vCPU 448GB RAM 6041GB Storage | Texas | $0.79/GPU/hr $6.32/hr total (8×) | Available |
When to Choose the L40
Choose the L40 for workloads demanding high VRAM and FP32 compute, such as training large language models requiring 48 GB capacity or scientific simulations leveraging 90.5 TFLOPS single-precision performance. Its Ada Lovelace architecture ensures compatibility with latest CUDA libraries and PCIe form factor simplifies cloud integration. At $0.67 per hour starting price, it justifies premium for contemporary AI pipelines.
When to Choose the Tesla V100 16GB
Opt for the V100 16GB in budget-constrained scenarios with FP16-heavy inference, where 125 TFLOPS half-precision throughput and $0.10 per hour entry pricing deliver value across 25 cloud offers. Legacy Volta-optimized codebases benefit from NVLink interconnect and HBM2's 900 GB/s bandwidth. It suits smaller-scale tasks fitting within 16 GB VRAM without needing modern features.
Use Cases
L40's 48 GB VRAM handles massive models without fragmentation, unlike V100's 16 GB limit. Its 90.5 TFLOPS FP32 supports precise gradient computations essential for training stability.
48 GB capacity on L40 accommodates larger batch sizes for high-throughput serving. Balanced 90.5 TFLOPS FP16/FP32 outperforms V100 in mixed-precision modern inference.
L40's superior 90.5 TFLOPS FP32 accelerates parameter updates on datasets fitting 48 GB VRAM. V100's lower capacity restricts model scales.
48 GB VRAM on L40 enables high-resolution image generation with large batches. 90.5 TFLOPS FP16 matches diffusion model demands better than V100's memory constraints.
L40 excels in FP32-heavy simulations at 90.5 TFLOPS with 48 GB for complex datasets. V100 suffices for FP16-optimized codes at 125 TFLOPS if VRAM needs stay under 16 GB.
Frequently Asked Questions
What is the VRAM difference between L40 and V100 16GB?▾
The L40 provides 48 GB GDDR6 VRAM, three times the V100 16GB's 16 GB HBM2 capacity. This enables L40 to manage larger AI models without memory errors. Bandwidth is close at 864 GB/s for L40 and 900 GB/s for V100.
How do FP32 performances compare?▾
L40 delivers 90.5 TFLOPS FP32, far surpassing V100's 15.7 TFLOPS. This gap favors L40 in training and simulations requiring single precision. V100 compensates in FP16 at 125 TFLOPS versus L40's 90.5 TFLOPS.
What are the cloud pricing ranges?▾
L40 starts at $0.67 per hour with an average of $0.89 across 14 offers. V100 16GB begins at $0.10 per hour, averaging $0.81 over 25 offers. Pricing reflects L40's newer architecture.
Which has higher memory bandwidth?▾
V100 edges out with 900 GB/s HBM2 bandwidth over L40's 864 GB/s GDDR6. Differences minimally impact most workloads given similar TDPs of 300W. Larger VRAM on L40 often compensates.
Are both GPUs suitable for PCIe systems?▾
Both support PCIe form factors, with V100 also offering SXM2 and NVLink. L40's PCIe design fits standard cloud servers seamlessly. Architectures differ: Ada Lovelace for L40, Volta for V100.
When is V100 still viable despite age?▾
V100 remains relevant for FP16 inference at 125 TFLOPS and low $0.10 per hour pricing. It handles legacy workloads within 16 GB VRAM effectively. Newer tasks favor L40's 48 GB and balanced compute.
Which is cheaper to rent, the L40 or the V100?▾
Cloud rental prices for both the L40 and V100 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 V100?▾
The L40 has 48 GB of GDDR6 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find L40 and V100 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 V100?▾
The L40 uses the Ada Lovelace architecture (2023) while the V100 uses Volta (2017). The V100 delivers 1.4x the FP16 throughput and 1.0x the memory bandwidth of the L40.