NVIDIA A100 SXM4 80GB HBM2e Datacenter GPU
Brand: NVIDIA | Category: GPUs
SKU: 900-21001-0004-000 | Part #: 900-21001-0004-000 | MPN: 900-21001-0004-000
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About the NVIDIA A100 SXM4 80GB HBM2e Datacenter GPU
The NVIDIA A100 SXM4 80GB HBM2e is a passive OAM-cooled datacenter GPU engineered for scale-out AI, machine learning, and high-performance computing deployments. Built on the proven NVIDIA Ampere architecture, this accelerator (part number 900-21001-0004-000) delivers exceptional performance density with 6,912 CUDA cores and 432 third-generation Tensor Cores, making it the platform of choice for AI infrastructure teams and data center architects worldwide.
With 80GB of ultra-fast HBM2e memory and 2 TB/s memory bandwidth, the A100 SXM4 excels at training large language models, recommendation engines, and complex simulations. The GPU's third-generation Tensor Cores accelerate mixed-precision workloads across FP64, FP32, TF32, FP16, BF16, and INT8 formats, reaching up to 624 TFLOPS for sparse tensor operations. NVIDIA's NVLink 3.0 interconnect delivers 600 GB/s bidirectional bandwidth for multi-GPU scaling, while Multi-Instance GPU (MIG) technology enables up to seven isolated 10GB instances per card—maximizing resource utilization in shared environments. Full ECC memory support and PCIe Gen 4 integration ensure enterprise-grade reliability and compatibility with existing server infrastructure. At 400W TDP, the A100 SXM4 integrates seamlessly into optimized cooling environments. Whether you're building GPU clusters for research institutions, deploying inference infrastructure for production AI services, or scaling training pipelines, NVIDIA's A100 delivers proven ROI across industries. Omnixon Global is your authorized distributor partner in the UAE and greater Middle East region. Contact us for a detailed RFQ on NVIDIA A100 SXM4 GPUs and volume pricing tailored to your deployment requirements.
Key Specifications
- Part Number: 900-21001-0004-000
- GPU Memory: 80 GB HBM2e with ECC support
- CUDA Cores / Tensor Cores: 6,912 / 432 (3rd Gen)
- Peak Tensor Performance: 624 TFLOPS (FP16/BF16/TF32 sparse)
- NVLink 3.0 Bandwidth: 600 GB/s bidirectional
- Multi-Instance GPU: Up to 7 × 10GB partitions per card
Technical Specifications
| Brand | NVIDIA |
| Category | GPUs |
| SKU | 900-21001-0004-000 |
| Part Number | 900-21001-0004-000 |
| Condition | New |
| Manufacturer Part Number | 900-21001-0004-000 |
| GPU Architecture | NVIDIA Ampere |
| Form Factor | SXM4 |
| CUDA Cores | 6912 |
| Tensor Cores | 432 (3rd Generation) |
| GPU Memory | 80 GB HBM2e |
| Memory Bandwidth | 2 TB/s |
| FP64 Performance | 9.7 TFLOPS |
| FP32 Performance | 19.5 TFLOPS |
| TF32 Tensor Core Performance | 312 TFLOPS (sparse: 624 TFLOPS) |
| FP16 Tensor Core Performance | 312 TFLOPS (sparse: 624 TFLOPS) |
| BF16 Tensor Core Performance | 312 TFLOPS (sparse: 624 TFLOPS) |
| INT8 Tensor Core Performance | 624 TOPS (sparse: 1248 TOPS) |
| NVLink Interconnect Bandwidth | 600 GB/s (bidirectional) |
| NVLink Version | NVLink 3.0 |
| PCIe Interface | PCIe Gen 4 |
| Multi-Instance GPU (MIG) | Up to 7 MIG instances (10GB each) |
| Thermal Design Power (TDP) | 400 W |
| ECC Memory Support | Yes |
Frequently Asked Questions about NVIDIA A100 SXM4 80GB HBM2e Datacenter GPU
What server platforms accept the NVIDIA A100 SXM4 80GB HBM2e Datacenter GPU?
Reference servers include Dell PowerEdge XE9680 / XE9712, HPE Cray XD670, Lenovo ThinkSystem SR685a / SR675 V3, Supermicro AS-A21GE / SYS-821GE, Gigabyte G593 / G894, ASUS ESC. Share your target platform in the RFQ and we will confirm chassis-to-GPU compatibility and recommended NIC pairing.
How long is the lead time on AI GPUs?
Highly model-dependent. L40S / RTX-class: typically 3-6 weeks. H100/H200/B200 in SXM form factor: 12-16 weeks for whole-platform allocations. We quote genuine-channel ETAs only — no grey-market promises.
Do you supply matched networking (Quantum InfiniBand / Spectrum-X)?
Yes — Omnixon stocks the full NVIDIA networking lineup (Quantum-2 / Quantum-X InfiniBand, Spectrum-X Ethernet, ConnectX NICs, BlueField DPUs) so we can quote a complete training-cluster BOM, not just the GPUs.
Can you help with NVIDIA AI Enterprise licensing?
Yes. We hold genuine-channels for NVIDIA AI Enterprise software subscriptions. Add it to your RFQ and we quote node-aligned licensing along with the hardware.