NVIDIA A100 80GB
The NVIDIA A100 80GB is a flagship Ampere-based training GPU featuring 80GB HBM2e memory, third-generation Tensor Cores, and Multi-Instance GPU (MIG) technology. Available in both SXM and PCIe form factors, it serves as the go-to compute platform for large-scale model training, fine-tuning, and HPC. In the domestic market, the A800 variant offers NVLink bandwidth adjusted to 400 GB/s.
Core Specifications
CompleteSpecifications
| architecture | Ampere |
| Shape | SXM4 / PCIe Dual Slot |
| TF32 Tensor Core | 312 TFLOPS* (sparse) |
| VRAM | 8 0GB HBM2e |
| Memory Bandwidth | 2,039 GB/s (SXM) | 1,935 GB/s (PCIe) |
| Power Consumption | 400W (SXM) | 300W (PCIe) |
| Location | Large Model Training/Fine-tuning, HPC, Scientific Computing |
| China-Specific Edition | A800 (NVLink bandwidth adjusted to 400 GB/s) |
| MIG | Maximum of 7 instances |
| NVLink | 3rd Gen NVLink, 600 GB/s |
| FP16/BF16 Tensor Core | 624 TFLOPS* (sparse) |
| FP64 | 9.7 TFLOPS | FP64 Tensor Core 19.5 TFLOPS |
* Sparse mode specifications: Dense performance is half that of sparse specs. Specs sourced from NVIDIA's official product page; actual configuration subject to factory settings.
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The NVIDIA A100 80GB is a flagship Ampere-based training GPU featuring 80GB HBM2e memory, third-generation Tensor Cores, and Multi-Instance GPU (MIG) technology. Available in both SXM and PCIe form factors, it serves as the go-to compute platform for large-scale model training, fine-tuning, and HPC. In the domestic market, the A800 variant offers NVLink bandwidth adjusted to 400 GB/s.
| architecture | Ampere |
| Shape | SXM4 / PCIe Dual Slot |
| TF32 Tensor Core | 312 TFLOPS* (sparse) |
| VRAM | 8 0GB HBM2e |
| Memory Bandwidth | 2,039 GB/s (SXM) | 1,935 GB/s (PCIe) |
| Power Consumption | 400W (SXM) | 300W (PCIe) |
| Location | Large Model Training/Fine-tuning, HPC, Scientific Computing |
| China-Specific Edition | A800 (NVLink bandwidth adjusted to 400 GB/s) |
| MIG | Maximum of 7 instances |
| NVLink | 3rd Gen NVLink, 600 GB/s |
| FP16/BF16 Tensor Core | 624 TFLOPS* (sparse) |
| FP64 | 9.7 TFLOPS | FP64 Tensor Core 19.5 TFLOPS |
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