NVIDIA B200 VS NVIDIA L40S
Choosing between **B200** and **L40S** depends on your specific AI workload requirements. While the **B200** offers more VRAM for larger models, the **L40S** remains competitive in other areas. Currently, you can rent these GPUs starting from **$2.25/h** and **$0.26/h** respectively across 52 providers.
📊 Detailed Specifications Comparison
| Specification | B200 | L40S | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Blackwell | Ada Lovelace | - |
| Process Node | 4nm | 4nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | SXM | Dual-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 192GB | 48GB | +300% |
| Memory Type | HBM3e | GDDR6 | - |
| Memory Bandwidth | 8.0 TB/s | 864 GB/s | +826% |
| Memory Bus Width | 8192-bit | 384-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 18,432 | 18,176 | +1% |
| Tensor Cores (AI) | 576 | 568 | +1% |
| RT Cores (Ray Tracing) | N/A | 142 | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 90 TFLOPS | 91.6 TFLOPS | -2% |
| FP16 (Half Precision) | 4,500 TFLOPS | 183.2 TFLOPS | +2356% |
| TF32 (Tensor Float) | 2,250 TFLOPS | N/A | |
| FP64 (Double Precision) | 45 TFLOPS | N/A | |
| INT8 (Integer Precision) | 9,000 TOPS | 733 TOPS | +1128% |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 1000W | 350W | +186% |
| PCIe Interface | PCIe 5.0 x16 | PCIe 4.0 x16 | - |
| Multi-GPU Interconnect | NVLink 5.0 (1.8 TB/s) | None | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA B200
Higher VRAM capacity and memory bandwidth are critical for training large language models. The B200 offers 192GB compared to 48GB.
AI Inference
NVIDIA B200
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA L40S
Based on current cloud pricing, the L40S starts at a lower hourly rate.
Technical Deep Dive: B200 vs L40S
This is a generational comparison within the NVIDIA ecosystem, pitting Blackwell against Ada Lovelace. The B200 has a significant **144GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **L40S** is currently about **88% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA B200 is Best For:
- Next-gen LLM training
- Trillion parameter models
- Cost-sensitive projects
NVIDIA L40S is Best For:
- AI inference
- Generative AI
- Maximum memory bandwidth
Frequently Asked Questions
Which GPU is better for AI training: B200 or L40S?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The B200 offers 192GB of HBM3e memory with 8.0 TB/s bandwidth, while the L40S provides 48GB of GDDR6 with 864 GB/s bandwidth. For larger models, the B200's higher VRAM capacity gives it an advantage.
What is the price difference between B200 and L40S in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, B200 starts at $2.25/hour while L40S starts at $0.26/hour. This represents a 765% price difference.
Can I use L40S instead of B200 for my workload?
It depends on your specific requirements. If your model fits within 48GB of VRAM and you don't need the additional throughput of the B200, the L40S can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the B200's NVLink support (NVLink 5.0 (1.8 TB/s)) may be essential.
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