Specifications Compared
| Spec | B200 | L40S |
|---|---|---|
| TDP | 1000W | 350W |
| VRAM | 192 GB | 48 GB |
| CUDA Cores | 18,432 | 18,176 |
| Memory Type | HBM3e | GDDR6X |
| Architecture | Blackwell | Ada Lovelace |
| Form Factors | SXM, NVL | PCIe |
| Interconnect | NVLink, PCIe 6.0, InfiniBand | PCIe 4.0 |
| Tensor Cores | 576 | 568 |
| FP8 Performance | 9,000 TFLOPS | 724 TFLOPS |
| FP16 Performance | 4,500 TFLOPS | 362 TFLOPS |
| FP32 Performance | 90 TFLOPS | 91 TFLOPS |
| FP64 Performance | 45 TFLOPS | 1.4 TFLOPS |
| INT8 Performance | 9,000 TOPS | 724 TOPS |
| Memory Bandwidth | 8,000 GB/s | 864 GB/s |
Performance Analysis
Compute performance favors the B200 decisively in mixed-precision tasks: its 4500 TFLOPS FP16 capability outpaces the L40S's 362 TFLOPS by over 12 times, accelerating LLM training where tensor operations dominate. FP32 rates remain close at 90 TFLOPS for B200 and 91 TFLOPS for L40S, suggesting similar suitability for traditional scientific simulations requiring single-precision arithmetic. FP8 performance underscores inference advantages, with B200 at 9000 TFLOPS versus L40S at 724 TFLOPS, enabling higher throughput for quantized large language models.
Memory bandwidth profoundly impacts real-world usage: the B200's 8000 GB/s allows batch sizes up to 10 times larger than the L40S's 864 GB/s limit, reducing training iterations and latency in memory-bound workloads like fine-tuning. Higher TDP of 1000W on B200 demands robust cooling compared to L40S's efficient 350W, influencing deployment in dense clusters. Interconnects further differentiate: B200 supports NVLink and PCIe 6.0 for multi-GPU scaling, while L40S sticks to PCIe 4.0, constraining large-scale training efficiency.
These specs translate to B200 handling models exceeding 100 billion parameters seamlessly, whereas L40S suits sub-30 billion parameter inference with lower overhead.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
B200
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Nebius | NVIDIA B200 SXM 192GB VRAM | 192GB | 20 vCPU 224GB RAM | 🌍Europe | $3.95/GPU/hr | |||
 Cirrascale | 8×NVIDIA B200 SXM 192GB VRAM | 192GB | 192 vCPU 2048GB RAM 43923GB Storage | United States | $4.79/GPU/hr $38.32/hr total (8×) | |||
Cirrascale | 8×NVIDIA B200 SXM 192GB VRAM | 192GB | 192 vCPU 2048GB RAM 43923GB Storage | United States | $5.39/GPU/hr $43.12/hr total (8×) | |||
Cirrascale | 8×NVIDIA B200 SXM 192GB VRAM | 192GB | 192 vCPU 2048GB RAM 43923GB Storage | United States | $5.69/GPU/hr $45.52/hr total (8×) | |||
 RunPod | NVIDIA B200 SXM 192GB VRAM | 192GB | 28 vCPU 283GB RAM | North Carolina | $5.89/GPU/hr |
L40S
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA L40S 48GB VRAM | 48GB | 0 vCPU 0GB RAM | Wolverhampton | $0.55/GPU/hr | Available | ||
RunPod | NVIDIA L40S 48GB VRAM | 48GB | 16 vCPU 94GB RAM | 🌍global | $0.86/GPU/hr | |||
 Massed Compute | NVIDIA L40S 48GB VRAM | 48GB | 12 vCPU 72GB RAM 625GB Storage | Iowa | $0.88/GPU/hr | Available | ||
Massed Compute | 2×NVIDIA L40S 48GB VRAM | 48GB | 24 vCPU 144GB RAM 1250GB Storage | Iowa | $0.88/GPU/hr $1.76/hr total (2×) | Available | ||
Massed Compute | NVIDIA L40S 48GB VRAM | 48GB | 12 vCPU 72GB RAM 625GB Storage | Iowa | $0.88/GPU/hr | Available |
When to Choose the B200
Opt for the B200 in scenarios demanding extreme scale: LLM training on models requiring over 100 GB VRAM benefits from its 192 GB HBM3e and 4500 TFLOPS FP16. High-throughput inference workloads leverage 9000 TFLOPS FP8 and 8000 GB/s bandwidth for serving thousands of requests per second.
Multi-GPU clusters thrive with NVLink and PCIe 6.0 interconnects, justifying $4.89 per hour pricing for enterprises prioritizing speed over cost.
When to Choose the L40S
The L40S suits budget-conscious deployments: its $1.65 per hour pricing delivers 362 TFLOPS FP16 for fine-tuning smaller models under 48 GB VRAM needs. Lower 350W TDP enables dense rack configurations without extensive power infrastructure.
Inference on quantized models or Stable Diffusion tasks performs adequately with 724 TFLOPS FP8, offering value where B200's capacity remains underutilized.
Use Cases
B200's 192 GB HBM3e VRAM and 4500 TFLOPS FP16 handle massive datasets and models exceeding L40S's 48 GB limit. Bandwidth of 8000 GB/s supports large batch sizes critical for efficient training.
9000 TFLOPS FP8 on B200 delivers higher throughput for serving large models compared to L40S's 724 TFLOPS. 192 GB VRAM accommodates full model loading without sharding.
B200's superior 4500 TFLOPS FP16 and memory capacity accelerate iterations on parameter-heavy models. L40S suffices only for smaller datasets under 48 GB.
L40S's 362 TFLOPS FP16 and 48 GB VRAM meet image generation needs at $1.65 per hour. B200's overkill capacity adds unnecessary $4.89 per hour cost.
Comparable FP32 at 91 TFLOPS on L40S matches B200's 90 TFLOPS for simulations, with 350W TDP enabling cost-effective scaling. Lower pricing favors prolonged runs.
Frequently Asked Questions
Which GPU has more VRAM, B200 or L40S?▾
The B200 provides 192 GB HBM3e VRAM, surpassing the L40S's 48 GB GDDR6X by four times. This enables B200 to load larger AI models without memory swapping. L40S remains suitable for mid-sized workloads.
How do B200 and L40S compare in FP16 performance?▾
B200 achieves 4500 TFLOPS FP16, over 12 times the L40S's 362 TFLOPS. This gap accelerates deep learning training significantly on B200. FP32 rates are similar at 90 TFLOPS versus 91 TFLOPS.
What is the price difference between B200 and L40S in the cloud?▾
B200 starts at $4.89 per hour averaging $5.03 across three offers, while L40S begins at $1.65 averaging $1.66. B200 suits high-performance needs despite the premium. L40S offers better value for lighter tasks.
Does B200 or L40S have higher memory bandwidth?▾
B200 delivers 8000 GB/s bandwidth, nearly ten times the L40S's 864 GB/s. Higher bandwidth on B200 supports larger batches in training. This impacts data-intensive AI pipelines directly.
Which GPU is better for LLM inference?▾
B200 excels with 9000 TFLOPS FP8 and 192 GB VRAM for high-throughput serving of large models. L40S's 724 TFLOPS FP8 handles smaller quantized models adequately. Choose based on model size and latency needs.
What are the TDP ratings for B200 and L40S?▾
B200 requires 1000W TDP, demanding advanced cooling, versus L40S's efficient 350W. Lower TDP on L40S facilitates denser deployments. Power differences affect cluster design choices.
Which is cheaper to rent, the B200 or the L40S?▾
Cloud rental prices for both the B200 and L40S 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 L40S?▾
The B200 has 192 GB of HBM3e memory. The L40S has 48 GB of GDDR6X memory.
Can I find B200 and L40S 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 L40S?▾
The B200 uses the Blackwell architecture (2024) while the L40S uses Ada Lovelace (2023). The L40S delivers 0.1x the FP16 throughput and 0.1x the memory bandwidth of the B200.