NVIDIA GB300vsNVIDIA H100 SXM
Comprehensive comparison for AI, machine learning, and high-performance computing workloads.
NVIDIA GB300
Blackwell Architecture
NVIDIA H100 SXM
Hopper Architecture
Detailed Specifications
| Specification | NVIDIA GB300 | NVIDIA H100 SXM |
|---|---|---|
| Architecture | Blackwell | Hopper |
| Release Year | 2025 | 2022 |
| VRAM | 256 GB+220.0% | 80 GB |
| Memory Type | HBM3e | HBM3 |
| Memory Bandwidth | 10000 GB/s+198.5% | 3350 GB/s |
| FP32 Performance | 120 TFLOPS+100.0% | 60 TFLOPS |
| FP16 Performance | 240 TFLOPS+100.0% | 120 TFLOPS |
| INT8 Performance | 4800 TOPS+100.0% | 2400 TOPS |
| Tensor Cores | 20480 | 16896 |
| CUDA Cores | N/A | 16896 |
| TDP | 1200W | 700W |
| Form Factor | SXM | SXM |
| NVLink Support | Yes | Yes |
| Avg. Price/Hour | $4.25+183.3% | $1.5 |
Performance Breakdown
Compute Performance
Single-precision floating-point performance for general compute workloads
NVIDIA GB300 is 100% faster
AI Training Performance
Half-precision performance optimized for deep learning training
NVIDIA GB300 is 100% faster
AI Inference Performance
Integer performance for efficient model inference and deployment
NVIDIA GB300 is 100% faster
Memory Bandwidth
Data transfer speed between GPU and memory
NVIDIA GB300 is 198.5% faster
NVIDIA GB300
NVIDIA GB300
NVIDIA H100 SXM
NVIDIA GB300
Ideal Workloads
NVIDIA GB300
NVIDIA H100 SXM
Cost Analysis
Hourly Rate
Daily Cost
Monthly Cost
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Frequently Asked Questions
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