Comprehensive comparison for AI, machine learning, and high-performance computing workloads.
Ampere Architecture
Ada Lovelace Architecture
| Specification | NVIDIA A100 PCIe | NVIDIA RTX 4080 |
|---|---|---|
| Architecture | Ampere | Ada Lovelace |
| Release Year | 2020 | 2022 |
| VRAM | 80 GB+400.0% | 16 GB |
| Memory Type | HBM2e | GDDR6X |
| Memory Bandwidth | 1935 GB/s+162.9% | 736 GB/s |
| FP32 Performance | 19.5 TFLOPS | 48.7 TFLOPS+60% |
| FP16 Performance | 78 TFLOPS | 97.4 TFLOPS+19.9% |
| INT8 Performance | 624 TOPS+60.0% | 390 TOPS |
| Tensor Cores | 6912 | 9728 |
| CUDA Cores | 6912 | 9728 |
| TDP | 300W | 320W |
| Form Factor | PCIe | Consumer |
| NVLink Support | No | No |
| Avg. Price/Hour | $0.98+180.0% | $0.35 |
Single-precision floating-point performance for general compute workloads
NVIDIA RTX 4080 is 60% faster
Half-precision performance optimized for deep learning training
NVIDIA RTX 4080 is 19.9% faster
Integer performance for efficient model inference and deployment
NVIDIA A100 PCIe is 60% faster
Data transfer speed between GPU and memory
NVIDIA A100 PCIe is 162.9% faster
NVIDIA RTX 4080
NVIDIA A100 PCIe
NVIDIA RTX 4080
NVIDIA RTX 4080
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