GPU comparison

L40 vs Quadro RTX 8000

Specifications and current cloud pricing, side by side.

Ada LovelacevsTuringUpdated 34 days ago

The L40 wins for the most common single-GPU training and inference tasks. Its dense FP16 rating of 181.05 TFLOPS and FP32 rating of 90.5 TFLOPS exceed the Quadro RTX 8000 equivalents by substantial margins while the shared 48 GB memory capacity removes capacity as a differentiator.

L40 listed from $0.79/GPU/hr

Right now, from live stock

  • Cheapest right now: L40 at $0.79/hr on ThunderCompute

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  • Most providers in stock: L40 (4)

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Specifications Compared

SpecL40Quadro RTX 8000
TDP300W260W
VRAM48 GB48 GB
CUDA Cores18,1764,608
FP8 (dense)362 TFLOPSNot published
Memory TypeGDDR6GDDR6
ArchitectureAda LovelaceTuring
FP16 (dense)181.05 TFLOPS130.5 TFLOPS
Form FactorsPCIePCIe
INT8 (dense)362 TOPSNot published
InterconnectPCIe 4.0NVLink, PCIe 3.0
Tensor Cores568576
FP32 Performance90.5 TFLOPS16.3 TFLOPS
Memory Bandwidth864 GB/s672 GB/s
FP8 (with sparsity)724 TFLOPSNot published
FP16 (with sparsity)362.1 TFLOPSNot published
INT8 (with sparsity)724 TOPSNot published

Performance Analysis

Dense FP16 throughput reaches 181.05 TFLOPS on the L40 against 130.5 TFLOPS on the Quadro RTX 8000. The same dense FP16 advantage scales to training and inference steps where matrix operations dominate. FP32 performance of 90.5 TFLOPS on the L40 versus 16.3 TFLOPS on the Quadro RTX 8000 further widens the gap for single-precision scientific kernels. Memory bandwidth of 864 GB/s on the L40 versus 672 GB/s on the Quadro RTX 8000 permits larger batch sizes before memory stalls occur. When sparsity is enabled the L40 reaches 362.1 TFLOPS dense FP16 equivalent while the Quadro RTX 8000 provides no sparsity figure for comparison.

Current On-Demand Offers

Cheapest secure on-demand offer per provider that is reported in stock right now, per GPU per hour; multi-GPU instances show the whole-instance price alongside. Deploy opens the DeployGPU console for providers on the platform, otherwise the provider's own site. Stock is rechecked every minute.

L40

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
ThunderComputeUSA2$0.79$1.58Deploy
Massed Computeus-central-31$0.86—Deploy
QuantaCloudus-midwest-24$0.94$3.75Deploy
HyperstackCANADA-12$1.00$2.00Deploy

4 providers in stock, 16 offers (cheapest per provider shown). All L40 offers, price history and alerts

Quadro RTX 8000

Quadro RTX 8000 is not offered on-demand by any provider we track right now. See the Quadro RTX 8000 rental page for last-seen listed prices and a price alert.

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When to Choose the L40

The L40 suits workloads that require dense FP16 performance of 181.05 TFLOPS or FP32 performance of 90.5 TFLOPS. Its 864 GB/s bandwidth supports larger batches in inference pipelines that exceed the 672 GB/s limit of the older card. Newer Ada Lovelace architecture also supplies FP8 dense figures of 362 TFLOPS absent from the Quadro RTX 8000 specification.

When to Choose the Quadro RTX 8000

The Quadro RTX 8000 fits multi-GPU configurations that rely on NVLink connectivity unavailable on the L40. Its 260 W TDP allows denser rack packing where power budgets constrain 300 W cards. Established Turing drivers remain compatible with legacy professional software stacks that do not yet certify Ada Lovelace hardware.

Use Cases

LLM Training
L40

The L40 supplies dense FP16 performance of 181.05 TFLOPS against 130.5 TFLOPS on the Quadro RTX 8000.

LLM Inference
L40

Higher memory bandwidth of 864 GB/s on the L40 allows sustained throughput beyond the 672 GB/s limit of the Quadro RTX 8000.

Fine-tuning
L40

FP32 throughput of 90.5 TFLOPS on the L40 accelerates gradient calculations compared with 16.3 TFLOPS on the Quadro RTX 8000.

Stable Diffusion
L40

The L40 lists dense FP16 performance of 181.05 TFLOPS and supports sparsity up to 362.1 TFLOPS for diffusion workloads.

Scientific Computing
L40

FP32 performance reaches 90.5 TFLOPS on the L40 while the Quadro RTX 8000 remains at 16.3 TFLOPS.

Frequently Asked Questions

How does FP16 performance differ between the L40 and Quadro RTX 8000?▾

The L40 lists dense FP16 at 181.05 TFLOPS while the Quadro RTX 8000 lists 130.5 TFLOPS. Sparsity on the L40 doubles the figure to 362.1 TFLOPS.

What memory bandwidth do the two GPUs provide?▾

The L40 reaches 864 GB/s and the Quadro RTX 8000 reaches 672 GB/s. Both cards carry 48 GB GDDR6.

Which GPU offers higher FP32 throughput?▾

The L40 delivers 90.5 TFLOPS in FP32. The Quadro RTX 8000 delivers 16.3 TFLOPS in FP32.

Do the GPUs share the same power consumption?▾

The L40 carries a 300 W TDP. The Quadro RTX 8000 carries a 260 W TDP.

Which interconnect options exist on each card?▾

The L40 uses PCIe 4.0. The Quadro RTX 8000 supports NVLink together with PCIe 3.0.

Which is cheaper to rent, the L40 or the Quadro RTX 8000?▾

Cloud rental prices for both the L40 and Quadro RTX 8000 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 L40 have compared to the Quadro RTX 8000?▾

The L40 has 48 GB of GDDR6 memory. The Quadro RTX 8000 has 48 GB of GDDR6 memory.

Can I find L40 and Quadro RTX 8000 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 L40 and the Quadro RTX 8000?▾

The L40 uses the Ada Lovelace architecture (2023) while the Quadro RTX 8000 uses Turing (2018). The L40 delivers 1.4x the dense FP16 throughput (181.05 vs 130.5 TFLOPS, both without sparsity) and 1.3x the memory bandwidth of the Quadro RTX 8000.

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How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the L40 and the Quadro RTX 8000. Dense and sparse throughput are listed separately.
  • Prices and availability are live: every offer shown is an in-stock, on-demand listing from a provider we track, rechecked every minute.
  • The written comparison (overview, performance notes, when to choose each card, verdict, use cases and FAQ) was drafted with an AI model from the specification table above and passed an automated check that rejects any figure not in that table. It was last generated on . It contains no prices; those are always read live.
  • Read how we collect the data, or report an error on this page.

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