NVIDIA B200 VS NVIDIA B100
Choosing between **B200** and **B100** depends on your specific AI workload requirements. Currently, you can rent these GPUs starting from **$2.25/h** and **$0.00/h** respectively across 20 providers.
📊 Detailed Specifications Comparison
| Specification | B200 | B100 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Blackwell | Blackwell | - |
| Process Node | 4nm | 4nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | SXM | SXM | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 192GB | 192GB | |
| Memory Type | HBM3e | HBM3e | - |
| Memory Bandwidth | 8.0 TB/s | 8.0 TB/s | |
| Memory Bus Width | 8192-bit | 8192-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 18,432 | 14,336 | +29% |
| Tensor Cores (AI) | 576 | 448 | +29% |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 90 TFLOPS | 70 TFLOPS | +29% |
| FP16 (Half Precision) | 4,500 TFLOPS | 3,500 TFLOPS | +29% |
| TF32 (Tensor Float) | 2,250 TFLOPS | 1,750 TFLOPS | +29% |
| FP64 (Double Precision) | 45 TFLOPS | 35 TFLOPS | +29% |
| INT8 (Integer Precision) | 9,000 TOPS | 7,000 TOPS | +29% |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 1000W | 700W | +43% |
| PCIe Interface | PCIe 5.0 x16 | PCIe 5.0 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 B100 offers 192GB compared to 192GB.
AI Inference
NVIDIA B100
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA B200
Compare live pricing to find the best value for your specific workload.
Technical Deep Dive: B200 vs B100
Both GPUs utilize the NVIDIA Blackwell architecture. The primary difference lies in their compute core counts.
NVIDIA B200 is Best For:
- Next-gen LLM training
- Trillion parameter models
- Cost-sensitive projects
NVIDIA B100 is Best For:
- Large-scale AI training
- Budget deployments
Frequently Asked Questions
Which GPU is better for AI training: B200 or B100?
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 B100 provides 192GB of HBM3e with 8.0 TB/s bandwidth. Both GPUs have similar VRAM capacity, so performance characteristics become the deciding factor.
What is the price difference between B200 and B100 in the cloud?
Cloud GPU rental prices vary by provider and region. Check our price tracker for the latest rates from 50+ cloud providers.
Can I use B100 instead of B200 for my workload?
It depends on your specific requirements. If your model fits within 192GB of VRAM and you don't need the additional throughput of the B200, the B100 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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