L4 vs L40

Ada LovelacevsAda LovelaceUpdated 36 days ago

The L40 emerges as the winner for most common cloud AI use cases like LLM training and fine-tuning. Its 48 GB VRAM, 864 GB/s bandwidth, and 90.5 TFLOPS FP32 outperform L4's constraints in 24 GB VRAM and 30.3 TFLOPS FP32, justifying the price premium for capacity-demanding workloads.

L4 from $0.33/hrL40 from $0.55/hr

Specifications Compared

SpecL4L40
TDP72W300W
VRAM24 GB48 GB
CUDA Cores7,42418,176
Memory TypeGDDR6GDDR6
ArchitectureAda LovelaceAda Lovelace
Form FactorsPCIePCIe
InterconnectPCIe 4.0
Tensor Cores232568
FP8 Performance242 TFLOPS
FP16 Performance121 TFLOPS90.5 TFLOPS
FP32 Performance30.3 TFLOPS90.5 TFLOPS
FP64 Performance0.5 TFLOPS
INT8 Performance242 TOPS724 TOPS
Memory Bandwidth300 GB/s864 GB/s

Performance Analysis

Floating-point performance profiles shape workload efficiency. L4's 121 TFLOPS FP16 exceeds L40's 90.5 TFLOPS, enabling faster inference in mixed-precision setups common for LLMs. Conversely, L4's 30.3 TFLOPS FP32 trails L40's 90.5 TFLOPS, positioning L40 ahead for training phases reliant on single-precision accumulation.

L4's 242 TFLOPS FP8 further boosts quantized inference throughput. Memory bandwidth impacts data handling: L40's 864 GB/s supports larger batch sizes than L4's 300 GB/s, minimizing bottlenecks in model loading and processing for VRAM-intensive tasks.

Double VRAM on L40 (48 GB versus 24 GB) accommodates larger models without offloading, while L4's 72W TDP promotes higher density in power-limited clusters. These specs translate to L40 favoring memory-bound training and L4 excelling in efficient inference.

Live Cloud Pricing

Real-time prices from 25+ providers. Updated every 60 seconds.

L4

ProviderGPU ModelVRAMHost SpecsRegionPriceStatusAction
Vast.ai
Vast.ai
NVIDIA L4
24GB VRAM
$0.33/GPU/hr
Available
RunPod
RunPod
NVIDIA L4
24GB VRAM
$0.39/GPU/hr
TensorDock
TensorDock
NVIDIA L40S
48GB VRAM
$0.55/GPU/hr
Available
RunPod
RunPod
NVIDIA L40
48GB VRAM
$0.82/GPU/hr
RunPod
RunPod
NVIDIA L40S
48GB VRAM
$0.86/GPU/hr

L40

ProviderGPU ModelVRAMHost SpecsRegionPriceStatusAction
TensorDock
TensorDock
NVIDIA L40S
48GB VRAM
$0.55/GPU/hr
Available
RunPod
RunPod
NVIDIA L40
48GB VRAM
$0.82/GPU/hr
RunPod
RunPod
NVIDIA L40S
48GB VRAM
$0.86/GPU/hr
Massed Compute
Massed Compute
NVIDIA L40
48GB VRAM
$0.86/GPU/hr
Available
Massed Compute
Massed Compute
2×NVIDIA L40
48GB VRAM
$0.86/GPU/hr
$1.72/hr total (2×)
Available

Compare real-time pricing across 25+ providers

When to Choose the L4

The L4 stands out in low-power, high-density inference deployments. Its 72W TDP enables more GPUs per server compared to L40's 300W, ideal for edge cloud or cost-sensitive scaling. Starting at $0.32/hr, it delivers 121 TFLOPS FP16 and 242 TFLOPS FP8 for throughput-oriented serving of models fitting within 24 GB VRAM.

When to Choose the L40

The L40 proves superior for memory-heavy training and fine-tuning. With 48 GB GDDR6 VRAM and 864 GB/s bandwidth, it processes larger batches and models than L4's 24 GB and 300 GB/s. Balanced 90.5 TFLOPS FP16/FP32 supports diverse AI pipelines despite higher $0.67/hr starting cost.

Use Cases

LLM Training
L40

L40's 90.5 TFLOPS FP32 matches its FP16, outperforming L4's 30.3 TFLOPS FP32 for gradient computations. 48 GB VRAM handles larger models than L4's 24 GB.

LLM Inference
L4

L4's 121 TFLOPS FP16 and 242 TFLOPS FP8 exceed L40's 90.5 TFLOPS FP16 for mixed-precision serving. Lower 72W TDP and $0.32/hr pricing suit high-throughput deployments.

Fine-tuning
L40

L40's balanced 90.5 TFLOPS FP16/FP32 and 864 GB/s bandwidth enable efficient adapter training on large models. 48 GB VRAM exceeds L4's 24 GB for dataset handling.

Stable Diffusion
L40

L40's 48 GB VRAM supports high-resolution image generation without swapping, unlike L4's 24 GB limit. 864 GB/s bandwidth accelerates texture processing.

Scientific Computing
Either

L4 fits FP16-heavy simulations at 121 TFLOPS with 72W efficiency; L40 handles FP32-dominant tasks at 90.5 TFLOPS with 48 GB VRAM for complex datasets.

Frequently Asked Questions

What is the VRAM difference between L4 and L40?

L4 provides 24 GB GDDR6 VRAM, while L40 doubles it to 48 GB. This allows L40 to load larger models without offloading to system RAM.

How do L4 and L40 compare in FP16 performance?

L4 achieves 121 TFLOPS FP16, surpassing L40's 90.5 TFLOPS. L4's edge suits inference, but L40 balances with equal FP32 performance.

Which GPU has higher memory bandwidth?

L40 offers 864 GB/s, nearly three times L4's 300 GB/s. Higher bandwidth on L40 supports bigger batch sizes in training.

What are the power consumption and pricing differences?

L4 uses 72W TDP and starts at $0.32/hr (avg $0.68/hr across 15 offers); L40 requires 300W and $0.67/hr (avg $0.88/hr across 13). L4 favors efficiency-focused rentals.

Is L4 or L40 better for AI inference?

L4 excels with 121 TFLOPS FP16 and 242 TFLOPS FP8 at lower cost and power. L40 suits inference needing more than 24 GB VRAM.

Do both GPUs use the same architecture?

Yes, both employ Ada Lovelace from 2023 in PCIe form factors. Differences stem from tiering: L4 optimizes efficiency, L40 emphasizes capacity.

Which is cheaper to rent, the L4 or the L40?

Cloud rental prices for both the L4 and L40 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 L40?

The L4 has 24 GB of GDDR6 memory. The L40 has 48 GB of GDDR6 memory.

Can I find L4 and L40 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 L40?

The L4 uses the Ada Lovelace architecture (2023) while the L40 uses Ada Lovelace (2023). The L4 delivers 1.3x the FP16 throughput and 2.9x the memory bandwidth of the L40.