GPU Comparison

NVIDIA H100 vs L40S

Compare NVIDIA H100 and L40S across architecture, GPU memory, bandwidth, AI inference, training, infrastructure requirements and practical workload fit.

Daya ShankarLast verified: August 11, 2026Research methodology

NVIDIA Hopper

H100

GPU Memory

80 GB HBM3

Bandwidth

3.35 TB/s

High-end Hopper accelerator for AI training, large-model inference and HPC.

Explore NVIDIA H100
VS

NVIDIA Ada Lovelace

L40S

GPU Memory

48 GB GDDR6 ECC

Bandwidth

864 GB/s

Ada data-center GPU for generative AI inference, graphics, rendering and media workloads.

Explore NVIDIA L40S

H100 vs L40S at a Glance

Start with workload fit, then validate the choice against the exact cloud configuration and pricing available to you.

Choose H100 when

You need more than 48 GB of GPU memory.

Choose L40S when

48 GB is enough for the model or inference service.

Compare the full workload

Memory, bandwidth, precision, interconnects, media features, power and cloud price can all change the right answer.

NVIDIA H100 vs NVIDIA L40S Specifications

H100, H200 and A100 use SXM figures. B200 uses current NVIDIA HGX B200 specifications. L40S and L4 use their native PCIe card specifications, so each product is represented in its primary deployment form.

SpecificationNVIDIA H100NVIDIA L40S
ArchitectureNVIDIA HopperNVIDIA Ada Lovelace
GPU Memory80 GB HBM348 GB GDDR6 ECC
Memory Bandwidth3.35 TB/s864 GB/s
FP3267 TFLOPS91.6 TFLOPS
TF32 Tensor Core989 TFLOPS*366 TFLOPS*
FP16 / BF16 Tensor Core1,979 TFLOPS*733 TFLOPS*
FP8 Tensor Core3,958 TFLOPS*1,466 TFLOPS*
FP4 Tensor CoreNot natively supportedNot natively supported
NVLink900 GB/sNot supported
MIGUp to 7 MIGs @ 10 GBNot supported
Maximum PowerUp to 700 W350 W
Form FactorSXMDual-slot PCIe

* Tensor Core values marked with an asterisk are NVIDIA sparse specifications where applicable; dense performance is lower.

What Is the Main Difference Between NVIDIA H100 and NVIDIA L40S?

H100 and L40S target overlapping AI workloads but are built for different deployment priorities. H100 is a Hopper data-center accelerator centered on high-end AI and HPC, while L40S is an Ada Lovelace GPU designed to combine AI acceleration with RTX graphics and media capabilities.

H100 provides 80 GB HBM3 at 3.35 TB/s and 900 GB/s NVLink. L40S provides 48 GB GDDR6 at 864 GB/s, does not support NVLink or MIG, but adds third-generation RT Cores and dedicated media engines in a conventional PCIe form factor.

For large training or memory-intensive LLM serving, H100 has the stronger platform. For generative AI inference mixed with visualization, rendering or video, L40S can be the more appropriate resource.

Memory Capacity and Bandwidth

These specifications affect model fit, KV-cache headroom, batch size and memory-bound workloads.

GPU Memory

80 GB HBM3 vs 48 GB GDDR6 ECC
H100L40S

Memory Bandwidth

3.35 TB/s vs 864 GB/s
H100L40S

H100 vs L40S for LLM Inference

H100 has more memory and nearly four times the listed memory bandwidth, giving it more headroom for large models, long contexts and high batching. L40S still offers strong FP8 inference compute and can be attractive for models that fit within 48 GB.

H100 vs L40S for AI Training and HPC

H100 is the clear fit for large-scale training and HPC because it combines HBM3, NVLink, MIG and strong Hopper compute. L40S can train smaller models, but its GDDR6 memory system and lack of NVLink place it in a different scaling class.

H100 vs L40S for Graphics, Rendering and Media

L40S is the more versatile choice for graphics-heavy infrastructure. It includes third-generation RT Cores and multiple NVENC/NVDEC engines. H100 is designed as a compute accelerator rather than an RTX visualization GPU.

Which GPU Fits Your Workload?

Use this as directional guidance. Benchmark your own model and software stack before making a large infrastructure commitment.

WorkloadH100L40SDirection
Large LLM inferenceBest fitGoodH100
Small / medium generative AI inferenceExcellentExcellentDepends on price
Large-model trainingBest fitLimited by memory/scaleH100
HPCBest fitGeneral computeH100
3D rendering / visualizationNot primary focusBest fitL40S
Video AI / media pipelinesCapableBest fitL40S
PCIe deployment without NVLinkPossibleBest fitL40S

Cloud Pricing

Compare Current Provider Pricing

There is no single cloud price for either GPU. Rates vary by provider, region, server configuration, billing model and commitment. Compare current provider offers after you know which hardware class fits the workload.

H100 providers

Compare H100 pricing

View H100

L40S providers

Compare L40S pricing

View L40S

Final Decision

Should You Choose NVIDIA H100 or NVIDIA L40S?

Choose NVIDIA H100 if:

  • You need more than 48 GB of GPU memory.
  • Your workload is training-heavy or memory-bandwidth intensive.
  • NVLink or MIG matters to your infrastructure.
  • HPC is a major part of the workload mix.

Choose NVIDIA L40S if:

  • 48 GB is enough for the model or inference service.
  • You need RTX rendering, visualization or media acceleration.
  • You prefer a conventional PCIe GPU.
  • You want lower maximum power than H100 for inference-focused deployment.

H100 vs L40S FAQs

Common questions about choosing between these NVIDIA GPUs.

Which is better, NVIDIA H100 or L40S?
Choose H100 for large-model training, memory-heavy inference, HPC and NVLink scale-up. Choose L40S for inference, rendering, graphics and media when 48 GB is sufficient and a lower-power PCIe GPU is a better fit.
What is the main difference between H100 and L40S?
H100 uses Hopper with 80 GB HBM3 and 3.35 TB/s memory bandwidth, while L40S uses Ada Lovelace with 48 GB GDDR6 ECC and 864 GB/s. Tensor Core generation, precision support, interconnects and power can also differ.
Is H100 or L40S better for LLM inference?
H100 has more memory and nearly four times the listed memory bandwidth, giving it more headroom for large models, long contexts and high batching. L40S still offers strong FP8 inference compute and can be attractive for models that fit within 48 GB.
Which GPU is better for AI training, H100 or L40S?
H100 is the clear fit for large-scale training and HPC because it combines HBM3, NVLink, MIG and strong Hopper compute. L40S can train smaller models, but its GDDR6 memory system and lack of NVLink place it in a different scaling class.
How much memory do H100 and L40S have?
NVIDIA H100 provides 80 GB HBM3, while NVIDIA L40S provides 48 GB GDDR6 ECC. Memory capacity alone does not determine performance, so bandwidth, precision support and workload behavior should also be considered.
Which is cheaper to rent, H100 or L40S?
Cloud rental pricing for H100 and L40S varies by provider, region, configuration and billing model. Check current provider pricing rather than assuming one GPU is always cheaper.

Sources & Verification

Hardware specifications were checked against official NVIDIA product pages and documentation.

Last verified: August 11, 2026 · View our data source standards

GPU Profile

NVIDIA H100

See specifications, cloud providers, pricing and workload fit for H100.

View H100

GPU Profile

NVIDIA L40S

See specifications, cloud providers, pricing and workload fit for L40S.

View L40S