AI and graphics profile
NVIDIA L40S
Ada Lovelace · 48 GB PCIe
Memory
48 GB GDDR6 ECC
48 GB GDDR6 ECC
Bandwidth
864 GB/s
864 GB/s
FP32
91.6 TFLOPS
91.6 TFLOPS
TDP
350W
350W
Independently verified GPU comparison Updated July 15, 2025
NVIDIA L40S vs A100
Compare architecture, memory, AI performance, graphics capabilities and rental pricing to find the best GPU for your workload.
Memory and HPC profile
NVIDIA A100
Ampere · 80 GB SXM
Memory
80 GB HBM2e
80 GB HBM2e
Bandwidth
2,039 GB/s
2,039 GB/s
FP32
19.5 TFLOPS
19.5 TFLOPS
TDP
400W
400W
The honest take: Choose L40S for generative AI inference, rendering, video, virtual workstations and smaller training workloads that fit within 48 GB. Choose A100 when 80 GB memory, high bandwidth, FP64, MIG or NVLink matters. A100 costs only about 8% more in the starting AceCloud configurations, so workload requirements should decide the purchase.
Quick answer
Which GPU fits your workload?
A workload-first view of where L40S excels in generative AI and graphics and where A100 leads in memory-heavy compute.
Generative AI inference
LLM, image-generation and multimodal inference within 48 GB
L40S L40S supports FP8, the Transformer Engine and fourth-generation Tensor Cores. It is a strong choice for image generation, multimodal AI and LLM inference workloads that fit within 48 GB.
Memory-intensive AI training
Large models, activations and training states beyond 48 GB
A100 A100 provides 80 GB HBM2e and 2,039 GB/s bandwidth. It is better suited to models, activations and training configurations that exceed L40S’s 48 GB memory.
LoRA and QLoRA fine-tuning
Parameter-efficient tuning when models and runtime fit within 48 GB
L40S For models that fit within 48 GB, L40S provides strong FP16, BF16 and FP8 performance at a slightly lower monthly price. A100 becomes preferable when additional memory or multi-GPU communication is required.
HPC and scientific computing
FP64-heavy simulations, scientific modeling and parallel analytics
A100 A100 provides FP64 and FP64 Tensor Core acceleration, high-bandwidth memory and NVLink. L40S is not positioned as a double-precision HPC accelerator.
Rendering and virtual production
Ray-traced rendering, Omniverse and professional visualization
L40S L40S includes third-generation RT Cores, four DisplayPort outputs, three NVENC encoders and three NVDEC decoders. It is the clear choice for rendering, Omniverse, video and visualization.
Multi-tenant GPU infrastructure
Hardware-isolated GPU partitioning for shared environments
A100 A100 supports up to seven MIG instances. L40S supports NVIDIA vGPU software but does not support MIG, so it cannot provide the same hardware-level GPU partitioning.
Side by side
Full technical specifications
The table compares the AceCloud configurations: NVIDIA L40S 48 GB PCIe and NVIDIA A100 80 GB SXM.
NVIDIA L40s and NVIDIA A100 technical specification comparison
| Specification | NVIDIA L40S | NVIDIA A100 80 GB |
|---|---|---|
| Architecture | Ada Lovelace | Ampere |
| GPU memory | 48 GB GDDR6 ECC | 80 GB HBM2e |
| Memory bandwidth | 864 GB/s | 2,039 GB/s |
| FP64 | Not listed | 9.7 TFLOPS |
| FP64 Tensor Core | Not listed | 19.5 TFLOPS |
| FP32 | 91.6 TFLOPS | 19.5 TFLOPS |
| TF32 Tensor Core, dense | 183 TFLOPS | 156 TFLOPS |
| TF32 Tensor Core, sparse | 366 TFLOPS | 312 TFLOPS |
| BF16 Tensor Core, dense | 362.05 TFLOPS | 312 TFLOPS |
| BF16 Tensor Core, sparse | 733 TFLOPS | 624 TFLOPS |
| FP16 Tensor Core, dense | 362.05 TFLOPS | 312 TFLOPS |
| FP16 Tensor Core, sparse | 733 TFLOPS | 624 TFLOPS |
| FP8 Tensor Core, dense | 733 TFLOPS | Not supported |
| FP8 Tensor Core, sparse | 1,466 TFLOPS | Not supported |
| INT8 Tensor Core, dense | 733 TOPS | 624 TOPS |
| INT8 Tensor Core, sparse | 1,466 TOPS | 1,248 TOPS |
| Tensor Cores | Fourth generation | Third generation |
| Transformer Engine | Yes | No |
| RT Cores | 142 third-generation | Not listed |
| RT Core performance | 212 TFLOPS | Not listed |
| NVENC encoders | 3 | Not listed |
| NVDEC decoders | 3 | Not listed |
| AV1 encoding and decoding | Supported | Not listed |
| MIG support | No | Up to 7 instances at 10 GB |
| NVLink | No | 600 GB/s |
| PCIe interface | PCIe Gen4 x16, 64 GB/s | PCIe Gen4, 64 GB/s |
| Display outputs | 4× DisplayPort 1.4a | None listed |
| Form factor | Dual-slot PCIe | SXM |
| Maximum power | 350W | 400W standard configuration |
| AceCloud configurations | 1×, 2× and 4× GPUs | 1×, 2× and 4× GPUs |
H200 NVL costs ₹139,775 more monthly and includes twice the system RAM. The instance comparison is therefore not limited to GPU hardware alone.
Straight comparison
How do L40S and A100 performance differ?
Raw specifications translated into simple relative performance. Longer bars indicate higher output.
FP16 Tensor performance, with sparsity
TFLOPS A100
1.0×
L40S
1.17×
TF32 Tensor performance, with sparsity
TFLOPS A100
1.0×
L40S
1.17×
FP8 Tensor performance, with sparsity
TFLOPS A100
L40S
GPU memory capacity
GB L40S
1.0×
A100
1.67×
Memory bandwidth
GB/s L40S
1.0×
A100
2.36×
FP32 performance
TFLOPS A100
1.0×
L40S
4.7×
Monthly rental price
₹ L40S
A100
Disclaimer: These are theoretical specifications, not workload benchmarks. Performance depends on framework, precision, model architecture, batch size, software optimization and instance configuration.
What you pay
NVIDIA L40S vs A100 rental pricing
Current entry-level Noida pricing for Linux instances, excluding taxes:
NVIDIA L40S 48 GB
1× L40S cloud GPU instance
₹
83,000
/month
83,000
/month
- 16 vCPUs
- 64 GB RAM
- Six-month effective price: ₹78,850/month
- Twelve-month effective price: ₹74,700/month
- 1×, 2× and 4× configurations available
₹20,000 free credits · Spin up in <15 min
NVIDIA A100 80 GB
1× A100 cloud GPU instance
₹
90,000
/month
90,000
/month
- 16 vCPUs
- 128 GB RAM
- Six-month effective price: ₹85,500/month
- Twelve-month effective price: ₹81,000/month
- 1×, 2× and 4× configurations available
₹20,000 free credits · Help with setup
H200 NVL costs ₹139,775 more monthly and includes twice the system RAM. The instance comparison is therefore not limited to GPU hardware alone.
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