GPU comparison

B200 vs L4

Specifications and current cloud pricing, side by side.

BlackwellvsAda LovelaceUpdated 34 days ago

The B200 wins for the most common use case of LLM training because its 2250 TFLOPS dense FP16 rating and 8000 GB/s bandwidth exceed the L4 specifications by wide margins and support larger scale workloads effectively.

B200 from $8.23/GPU/hrL4 from $0.89/GPU/hr

Right now, from live stock

  • Cheapest right now: L4 at $0.89/hr on Scaleway

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  • Most providers in stock: B200 (3)

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  • Best $ per TFLOPS FP16 dense right now: B200 ($0.0037 per TFLOPS-hour at 2,250 TFLOPS)

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Specifications Compared

SpecB200L4
TDP1000W72W
VRAM180-192 GB24 GB
CUDA Cores18,4327,424
FP4 (dense)9,000 TFLOPSNot published
FP8 (dense)4,500 TFLOPS242 TFLOPS
Memory TypeHBM3eGDDR6
ArchitectureBlackwellAda Lovelace
FP16 (dense)2,250 TFLOPS121 TFLOPS
Form FactorsSXM, NVLPCIe
INT8 (dense)4,500 TOPS242 TOPS
InterconnectNVLink, PCIe 6.0, InfiniBandPCIe 4.0
Tensor Cores576232
FP32 Performance75 TFLOPS30.3 TFLOPS
FP64 Performance37 TFLOPS0.5 TFLOPS
Memory Bandwidth8,000 GB/s300 GB/s
FP4 (with sparsity)18,000 TFLOPSNot published
FP8 (with sparsity)9,000 TFLOPS485 TFLOPS
FP16 (with sparsity)4,500 TFLOPS242 TFLOPS
INT8 (with sparsity)9,000 TOPS485 TOPS

Performance Analysis

The FP16 dense performance reaches 2250 TFLOPS on the B200 compared with 121 TFLOPS on the L4 and the FP32 figures stand at 75 TFLOPS versus 30.3 TFLOPS. This FP16 dense to FP32 ratio supports accelerated matrix operations during training and inference workloads on the B200 while the L4 maintains a smaller ratio suited to lighter inference passes. Memory bandwidth of 8000 GB/s on the B200 versus 300 GB/s on the L4 permits substantially larger batch sizes in memory bound operations such as large model training. Dense FP16 figures must be compared directly against other dense FP16 values and sparsity figures against other sparsity values to maintain accuracy in projections.

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.

B200

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
VERDAFIN-HEL8$8.23$65.84Deploy
LyceumEurope1$8.79—Deploy
Vast.ai, US4$9.00$36.00Deploy

3 providers in stock, 4 offers (cheapest per provider shown). All B200 offers, price history and alerts

L4

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
ScalewayParis, France (PAR1)1$0.89—Deploy
Orilille-41$0.93—Deploy

2 providers in stock, 2 offers. All L4 offers, price history and alerts

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When to Choose the B200

The B200 suits scenarios that require the 2250 TFLOPS dense FP16 rating and 180 to 192 GB memory capacity for handling extensive model training runs. Its 8000 GB/s bandwidth further enables efficient scaling in multi GPU setups connected via NVLink.

When to Choose the L4

The L4 fits deployments where the 72W TDP and PCIe form factor allow integration into standard servers without specialized cooling. Its 121 TFLOPS dense FP16 rating handles moderate inference loads at lower overall power draw.

Use Cases

LLM Training
B200

The B200 provides 2250 TFLOPS dense FP16 performance against 121 TFLOPS on the L4 enabling faster completion of large scale training.

LLM Inference
B200

The B200 delivers 4500 TFLOPS dense FP8 performance compared with 242 TFLOPS on the L4 supporting higher throughput inference.

Fine-tuning
B200

The B200 memory capacity of 180 to 192 GB allows fine tuning of models that exceed the 24 GB limit of the L4.

Stable Diffusion
L4

The L4 72W TDP enables cost effective operation for image generation tasks that do not require the full capacity of the B200.

Scientific Computing
B200

The B200 FP32 rating of 75 TFLOPS combined with high bandwidth supports demanding simulation workloads beyond L4 capabilities.

Frequently Asked Questions

What is the FP16 dense performance of each GPU?▾

The B200 achieves 2250 TFLOPS in dense FP16 and the L4 achieves 121 TFLOPS in dense FP16.

How does memory bandwidth differ between the B200 and L4?▾

The B200 provides 8000 GB/s memory bandwidth whereas the L4 provides 300 GB/s memory bandwidth.

What are the TDP values for the B200 and L4?▾

The B200 has a TDP of 1000W and the L4 has a TDP of 72W.

What FP8 dense performance do the GPUs offer?▾

The B200 reaches 4500 TFLOPS in dense FP8 and the L4 reaches 242 TFLOPS in dense FP8.

Which is cheaper to rent, the B200 or the L4?▾

Cloud rental prices for both the B200 and L4 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 B200 have compared to the L4?▾

The B200 has 180 to 192 GB of HBM3e memory. The L4 has 24 GB of GDDR6 memory.

Can I find B200 and L4 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 B200 and the L4?▾

The B200 uses the Blackwell architecture (2024) while the L4 uses Ada Lovelace (2023). The B200 delivers 18.6x the dense FP16 throughput (2,250 vs 121 TFLOPS, both without sparsity) and 26.7x the memory bandwidth of the L4.

Rent these GPUs

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How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the B200 and the L4. 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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