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L40S vs A100

Explore a head to head comparison of specifications, performance, and pricing.

L40S

The NVIDIA L40S delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$5.06/hr
GPU VRAM48 GB
Cloud Availability7 clouds
System Memory1536 GB
CPU Cores142
Storage30.7 TB

A100

The NVIDIA A100 is a powerful Ampere-based GPU designed for AI training, inference, and high-performance computing workloads.

ManufacturerNVIDIA
GPU ArchitectureAmpere
Average Price$7.35/hr
GPU VRAM40 GB
Cloud Availability5 clouds
System Memory1800 GB
CPU Cores176
Storage13.6 TB

L40S vs A100: Which Should You Choose?

The L40S offers 48 GB of VRAM — 1.2× the 40 GB on the A100 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the L40S delivers 91.61 TFLOPS versus 77.97 TFLOPS on the A100 — 1.2× faster for mixed-precision training and inference. Memory bandwidth favors the L40S at 0.86 TB/s compared to 0.00 TB/s on the A100, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the L40S is built on Ada Lovelace while the A100 uses Ampere, reflecting different generational capabilities and optimizations. On Shadeform, the L40S starts from $0.74/hr versus $1.36/hr for the A100 — 84% more expensive — reflecting the performance premium. The L40S is available across 7 cloud providers on Shadeform compared to 5 for the A100, giving more options for region and pricing flexibility.

L40S — Best Use Cases

  • LLM inference and model serving
  • Image generation and diffusion models
  • Smaller fine-tuning runs
  • Cost-efficient GPU compute

Choose L40S when:

  • You need 48 GB+ VRAM for large models or long context windows
  • Cost efficiency is your primary concern
  • You are training large models or running high-throughput inference
  • You need flexibility across multiple cloud providers or regions

A100 — Best Use Cases

  • General-purpose deep learning training
  • Fine-tuning models up to 13B parameters
  • AI inference at moderate throughput
  • Computer vision and NLP workloads

Choose A100 when:

  • 40 GB VRAM is sufficient for your workload
  • Maximum performance justifies the higher cost
  • Your workload does not require peak FP16 throughput
  • Your preferred provider already has availability

See how the L40S & A100 compare

Compare detailed hardware specifications and average pricing for the L40S and A100.

Compare Hardware Specifications

L40SA100
GPU Type
L40S
A100
VRAM per GPU
48 GB
40 GB
Manufacturer
NVIDIA
NVIDIA
Architecture
Ada Lovelace
Ampere
Interconnect
PCIe Gen4
PCIe Gen4 or SXM4
Memory Bandwidth
864 GB/s
1.55 TB/s
FP16 TFLOPS
91.61 TFLOPS (1:1)
77.97 TFLOPS (4:1)
CUDA Cores
18176
6912
Tensor Cores
568 (4th Gen)
432 (3rd Gen)
RT Cores
142 (3rd Gen)
N/A
Base Clock
1110 MHz
765 MHz
Boost Clock
2520 MHz
1410 MHz
TDP
350W
250W-400W
Process Node
TSMC 4N
TSMC 7nm
Data Formats
INT4, INT8, FP8, BF16, FP16, TF32, FP32
INT8, BF16, FP16, TF32, FP32, FP64

Compare Average On-Demand Pricing

L40SA100
1 GPU
$1.28 /hr
$1.88 /hr
2 GPUs
$2.69 /hr
$4.38 /hr
4 GPUs
$5.37 /hr
$8.64 /hr
8 GPUs
$8.95 /hr
$14.90 /hr

Frequently Asked Questions: L40S vs A100

The main differences are VRAM (48 GB vs 40 GB), FP16 throughput (91.61 vs 77.97 TFLOPS), architecture (Ada Lovelace vs Ampere). The L40S uses the Ada Lovelace architecture while the A100 is based on Ampere, giving each GPU different generational capabilities.

The L40S is generally better for large language model training due to its higher throughput and 48 GB of VRAM, which allows fitting larger models or larger batch sizes in a single pass. For smaller models or fine-tuning tasks where cost matters more, both GPUs can be effective.

On Shadeform, the L40S is available from $0.74/hr. The A100 starts from $1.36/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.

The L40S has more VRAM at 48 GB, compared to 40 GB on the A100. Higher VRAM allows you to run larger models without quantization, use longer context windows, and process larger batch sizes — all of which improve throughput and reduce latency for memory-bound workloads.

Based on TFLOPS per dollar, the L40S offers better raw compute value at current Shadeform on-demand rates. However, the best choice depends on your specific workload — if you need the extra VRAM or throughput of the A100, paying the premium may be justified by faster job completion and lower total cost.

The L40S is currently available across 7 cloud providers on Shadeform's network, compared to 5 for the A100. Shadeform lets you deploy either GPU across all available providers from a single platform, so you can always find available capacity without manually checking each cloud.

Mixing different GPU types in a single training cluster is generally not recommended, as it creates performance bottlenecks where faster GPUs wait for slower ones. For best results, use a homogeneous cluster of either L40S or A100. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore L40S & A100 Instances

Browse available instances with L40S and A100 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.

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