GPU Comparison

NVIDIA H200 vs L40S

Compare NVIDIA H200 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

H200

GPU Memory

141 GB HBM3e

Bandwidth

4.8 TB/s

Memory-enhanced Hopper accelerator for large LLM inference, training and memory-intensive HPC.

Explore NVIDIA H200
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

H200 vs L40S at a Glance

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

Choose H200 when

You need 141 GB HBM3e or very high bandwidth.

Choose L40S when

48 GB is enough.

Compare the full workload

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

NVIDIA H200 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 H200NVIDIA L40S
ArchitectureNVIDIA HopperNVIDIA Ada Lovelace
GPU Memory141 GB HBM3e48 GB GDDR6 ECC
Memory Bandwidth4.8 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 @ 18 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 H200 and NVIDIA L40S?

H200 and L40S serve different parts of the data-center GPU market. H200 is a Hopper accelerator built around 141 GB HBM3e and 4.8 TB/s bandwidth. L40S is an Ada Lovelace PCIe GPU with 48 GB GDDR6 and 864 GB/s.

H200 supports NVLink and MIG, which matter for scale-up and multi-tenant compute. L40S does not support either, but it adds RTX-class RT Cores and media engines that H200 is not designed to replace.

For large AI models and HPC, H200 is the stronger choice. For inference combined with visualization, rendering or video, L40S can be more practical.

Memory Capacity and Bandwidth

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

GPU Memory

141 GB HBM3e vs 48 GB GDDR6 ECC
H200L40S

Memory Bandwidth

4.8 TB/s vs 864 GB/s
H200L40S

H200 vs L40S for LLM Inference

H200 offers nearly three times the memory capacity and more than five times the listed memory bandwidth. L40S is still a strong FP8 inference GPU for models that fit inside 48 GB.

H200 vs L40S for Training and HPC

H200 is designed for large training and HPC, with HBM3e, NVLink and MIG. L40S can handle AI training at smaller scale, but its PCIe-only topology and GDDR6 memory system make it a different class of accelerator.

H200 vs L40S for Graphics and Media

L40S has the advantage when the same GPU must support rendering, visualization or media. It includes third-generation RT Cores and multiple NVENC/NVDEC engines. H200 is optimized around compute, AI and HPC.

Which GPU Fits Your Workload?

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

WorkloadH200L40SDirection
Very large LLM inferenceBest fitLimited by 48 GBH200
Mid-size FP8 inferenceExcellentExcellentCompare economics
AI trainingBest fitModerate scaleH200
HPCBest fitGeneral computeH200
Rendering / visualizationNot primary focusBest fitL40S
Video / media AICapableBest fitL40S
PCIe-only server deploymentNVL variant possibleBest 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.

Final Decision

Should You Choose NVIDIA H200 or NVIDIA L40S?

Choose NVIDIA H200 if:

  • You need 141 GB HBM3e or very high bandwidth.
  • You are training large models.
  • You need NVLink or MIG.
  • HPC or large-scale LLM serving is the primary workload.

Choose NVIDIA L40S if:

  • 48 GB is enough.
  • You need RTX rendering or visualization.
  • Video encode/decode is part of the workload.
  • A 350 W PCIe deployment better fits your infrastructure.

H200 vs L40S FAQs

Common questions about choosing between these NVIDIA GPUs.

Which is better, NVIDIA H200 or L40S?
Choose H200 for very large LLM inference, training, HPC and high-bandwidth multi-GPU workloads. Choose L40S for 48 GB inference, RTX graphics, rendering and media pipelines where a PCIe GPU with lower power is the better operational fit.
What is the main difference between H200 and L40S?
H200 uses Hopper with 141 GB HBM3e and 4.8 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 H200 or L40S better for LLM inference?
H200 offers nearly three times the memory capacity and more than five times the listed memory bandwidth. L40S is still a strong FP8 inference GPU for models that fit inside 48 GB.
Which GPU is better for AI training, H200 or L40S?
H200 is designed for large training and HPC, with HBM3e, NVLink and MIG. L40S can handle AI training at smaller scale, but its PCIe-only topology and GDDR6 memory system make it a different class of accelerator.
How much memory do H200 and L40S have?
NVIDIA H200 provides 141 GB HBM3e, 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, H200 or L40S?
Cloud rental pricing for H200 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