{"product_id":"nvidia-tesla-a100-40gb-hbm2-5120-bit-pci-express-4-0-x16-1x-8-pin-graphics-card-900-21001-0000-000","title":"Nvidia Tesla A100 40GB HBM2 PCIe 4.0 900-21001-0000-000 | AI GPU Accelerator","description":"\u003ch2\u003eNVIDIA Tesla A100 40GB HBM2 PCIe 4.0 x16 GPU — 900-21001-0000-000\u003c\/h2\u003e\u003cp\u003eThe NVIDIA Tesla A100 40GB HBM2 (900-21001-0000-000) is NVIDIA's flagship Ampere-architecture data center GPU accelerator in PCIe form factor, featuring 40GB of HBM2 memory and 1,555 GB\/s memory bandwidth. Designed for AI training, deep learning inference, data analytics, and high-performance computing (HPC), the A100 delivers transformative performance across a wide range of scientific and enterprise workloads. The PCIe 4.0 x16 interface enables deployment in standard server platforms without requiring NVLink-based SXM form factor infrastructure.\u003c\/p\u003e\u003ch3\u003eKey Specifications\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003ePart Number \/ MPN:\u003c\/strong\u003e 900-21001-0000-000\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eManufacturer:\u003c\/strong\u003e NVIDIA\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eProduct Line:\u003c\/strong\u003e Tesla A100\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eArchitecture:\u003c\/strong\u003e Ampere (GA100)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMemory:\u003c\/strong\u003e 40GB HBM2\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMemory Bandwidth:\u003c\/strong\u003e 1,555 GB\/s\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMemory Bus Width:\u003c\/strong\u003e 5120-bit\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eInterface:\u003c\/strong\u003e PCI-Express 4.0 x16\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePower Connector:\u003c\/strong\u003e 1x 8-pin PCIe\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTDP:\u003c\/strong\u003e 250W\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCooling:\u003c\/strong\u003e Passive (requires server airflow)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eForm Factor:\u003c\/strong\u003e Full-height, full-length (FHFL) PCIe\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eCompute Performance\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eFP64 (Double Precision):\u003c\/strong\u003e 9.7 TFLOPS\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFP64 Tensor Core:\u003c\/strong\u003e 19.5 TFLOPS\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFP32 (Single Precision):\u003c\/strong\u003e 19.5 TFLOPS\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTF32 Tensor Core:\u003c\/strong\u003e 156 TFLOPS (312 TFLOPS with sparsity)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBFLOAT16 Tensor Core:\u003c\/strong\u003e 312 TFLOPS (624 TFLOPS with sparsity)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFP16 Tensor Core:\u003c\/strong\u003e 312 TFLOPS (624 TFLOPS with sparsity)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eINT8 Tensor Core:\u003c\/strong\u003e 624 TOPS (1,248 TOPS with sparsity)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMemory Bandwidth:\u003c\/strong\u003e 1,555 GB\/s\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eMemory\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eCapacity:\u003c\/strong\u003e 40GB HBM2\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBandwidth:\u003c\/strong\u003e 1,555 GB\/s\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBus Width:\u003c\/strong\u003e 5120-bit\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eECC:\u003c\/strong\u003e Yes — hardware ECC for data integrity\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eFeatures\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003eNVIDIA Ampere architecture with 3rd-gen Tensor Cores\u003c\/li\u003e\n\u003cli\u003eStructural sparsity support — up to 2x throughput on sparse AI models\u003c\/li\u003e\n\u003cli\u003eMulti-Instance GPU (MIG) — partition into up to 7 isolated GPU instances\u003c\/li\u003e\n\u003cli\u003eNVLink 3.0 support (via NVLink Bridge for multi-GPU PCIe configurations)\u003c\/li\u003e\n\u003cli\u003ePCIe 4.0 x16 — compatible with PCIe 3.0 servers at reduced bandwidth\u003c\/li\u003e\n\u003cli\u003ePassive cooling — designed for high-airflow data center environments\u003c\/li\u003e\n\u003cli\u003eSupports CUDA 11+, cuDNN, TensorRT, NCCL, and NVIDIA AI Enterprise\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003ePhysical \u0026amp; Environmental\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eForm Factor:\u003c\/strong\u003e Full-height, full-length (FHFL) dual-slot PCIe\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTDP:\u003c\/strong\u003e 250W\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePower Connector:\u003c\/strong\u003e 1x 8-pin PCIe\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCooling:\u003c\/strong\u003e Passive (server airflow required)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eOperating Temperature:\u003c\/strong\u003e 0°C to 35°C (inlet air)\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eCompatibility\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003eCompatible with PCIe 4.0 x16 and PCIe 3.0 x16 server slots\u003c\/li\u003e\n\u003cli\u003eSupported on major server platforms: Dell PowerEdge, HPE ProLiant, Lenovo ThinkSystem, Supermicro\u003c\/li\u003e\n\u003cli\u003eRequires 250W slot\/system power budget per GPU\u003c\/li\u003e\n\u003cli\u003eCompatible with NVIDIA AI Enterprise, CUDA 11.x\/12.x, PyTorch, TensorFlow, JAX, MXNet\u003c\/li\u003e\n\u003cli\u003eIdeal for AI\/ML training, LLM inference, HPC simulation, genomics, financial modeling, and scientific computing\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Nvidia","offers":[{"title":"Default Title","offer_id":50488740020465,"sku":"900-21001-0000-000","price":5175.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0814\/5652\/9649\/files\/dm_900-21001-0000-000_1.jpg?v=1790105820","url":"https:\/\/aeonfly.shop\/products\/nvidia-tesla-a100-40gb-hbm2-5120-bit-pci-express-4-0-x16-1x-8-pin-graphics-card-900-21001-0000-000","provider":"Aeonfly","version":"1.0","type":"link"}