NVIDIA A100 SXMvsNVIDIA GB300
Comprehensive comparison for AI, machine learning, and high-performance computing workloads.
NVIDIA A100 SXM
Ampere Architecture
NVIDIA GB300
Blackwell Architecture
Detailed Specifications
| Specification | NVIDIA A100 SXM | NVIDIA GB300 |
|---|---|---|
| Architecture | Ampere | Blackwell |
| Release Year | 2020 | 2025 |
| VRAM | 80 GB | 256 GB+68.8% |
| Memory Type | HBM2e | HBM3e |
| Memory Bandwidth | 2039 GB/s | 10000 GB/s+79.6% |
| FP32 Performance | 19.5 TFLOPS | 120 TFLOPS+83.8% |
| FP16 Performance | 78 TFLOPS | 240 TFLOPS+67.5% |
| INT8 Performance | 624 TOPS | 4800 TOPS+87% |
| Tensor Cores | 6912 | 20480 |
| CUDA Cores | 6912 | N/A |
| TDP | 400W | 1200W |
| Form Factor | SXM | SXM |
| NVLink Support | Yes | Yes |
| Avg. Price/Hour | $1.05 | $4.25+75.3% |
Performance Breakdown
Compute Performance
Single-precision floating-point performance for general compute workloads
NVIDIA GB300 is 83.8% faster
AI Training Performance
Half-precision performance optimized for deep learning training
NVIDIA GB300 is 67.5% faster
AI Inference Performance
Integer performance for efficient model inference and deployment
NVIDIA GB300 is 87% faster
Memory Bandwidth
Data transfer speed between GPU and memory
NVIDIA GB300 is 79.6% faster
NVIDIA GB300
NVIDIA GB300
NVIDIA A100 SXM
NVIDIA GB300
Ideal Workloads
NVIDIA A100 SXM
NVIDIA GB300
Cost Analysis
Hourly Rate
Daily Cost
Monthly Cost
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Frequently Asked Questions
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