{"product_id":"nvidia-tesla-t4-16gb-gddr6-gpu-ai-inference-virtualization-deep-learning-accelerator","title":"NVIDIA Tesla T4 16GB GDDR6 GPU | AI Inference, Virtualization \u0026 Deep Learning Accelerator","description":"\u003ch1\u003e\u003cstrong\u003eNVIDIA Tesla T4 16GB GPU - Optimized for AI Inference, Virtualization \u0026amp; Deep Learning\u003c\/strong\u003e\u003c\/h1\u003e\n\u003ch2\u003e\u003cstrong\u003eCompact, Energy-Efficient GPU for Data Centers and Virtual Workloads — Compatible \u003cbr\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003ePart Numbers: 900-2G183-0000-001 \/ P09571-001 \/ R0W29C \/ 490-BFHN \/ 490-BFLB \/ UCSC-GPU-T4-16\u003c\/span\u003e\u003c\/strong\u003e\u003c\/h2\u003e\n\u003chr\u003e\n\u003cp\u003eThe \u003cstrong\u003eNVIDIA Tesla T4 16GB GPU\u003c\/strong\u003e delivers exceptional performance for AI inference, deep learning, data analytics, and virtual desktop infrastructure (VDI).\u003cbr\u003eBuilt on the \u003cstrong\u003eTuring architecture\u003c\/strong\u003e, it’s designed for energy-efficient scalability across cloud, enterprise, and edge deployments.\u003c\/p\u003e\n\u003cp\u003eFeaturing \u003cstrong\u003e2,560 CUDA cores\u003c\/strong\u003e, \u003cstrong\u003e320 Tensor Cores\u003c\/strong\u003e, and \u003cstrong\u003e16GB GDDR6 memory\u003c\/strong\u003e, the Tesla T4 brings versatile acceleration for AI workloads — from natural language processing and recommendation systems to video analytics and high-density virtualization.\u003c\/p\u003e\n\u003cp\u003eIts \u003cstrong\u003elow-profile PCIe form factor\u003c\/strong\u003e and \u003cstrong\u003e70W power consumption\u003c\/strong\u003e make it ideal for high-density servers and edge AI environments.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompatible Part Numbers:\u003c\/strong\u003e\u003cbr\u003e900-2G183-0000-001, P09571-001, R0W29C, 490-BFHN, 490-BFLB, UCSC-GPU-T4-16 — all share identical specifications and performance.\u003c\/p\u003e\n\u003chr\u003e\n\u003ch3\u003e\n\u003cstrong\u003e⚙️ Product Specifications For NVIDIA Tesla T4 16GB GDDR6 GPU\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003ca href=\"https:\/\/www.nvidia.com\/content\/dam\/en-zz\/Solutions\/Data-Center\/tesla-t4\/t4-tensor-core-datasheet-951643.pdf\" target=\"_blank\" title=\"NVIDIA Tesla T4 16GB GDDR6 GPU - Specifications Sheet\" rel=\"noopener\"\u003eCLICK HERE FOR SPECIFICATIONS SHEET\u003c\/a\u003e\u003ca href=\"https:\/\/www.nvidia.com\/content\/dam\/en-zz\/Solutions\/Data-Center\/tesla-t4\/t4-tensor-core-datasheet-951643.pdf\" target=\"_blank\" title=\"NVIDIA Tesla T4 16GB GDDR6 GPU - Specifications Sheet\" rel=\"noopener\"\u003e\u003c\/a\u003e\u003c\/strong\u003e\n\u003c\/h3\u003e\n\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eSpecification\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth\u003e\u003cstrong\u003eDetails\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eGPU Architecture\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eNVIDIA Turing\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eCUDA Cores\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e2,560\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eTensor Cores\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e320\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eGPU Memory\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e16GB GDDR6\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eMemory Interface\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e256-bit\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eMemory Bandwidth\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e320 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eFP32 Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e8.1 TFLOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eFP16 Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e65 TFLOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eINT8 Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e130 TOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eINT4 Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e260 TOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eForm Factor\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eLow-profile, PCIe Gen3 x16\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003ePower Consumption\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e70W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eCooling Type\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003ePassive or active (OEM dependent)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eNVENC \/ NVDEC Support\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eYes (Video Encoding\/Decoding)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eVirtualization Support\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eNVIDIA GRID \/ vGPU Ready\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eThermal Solution\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eServer airflow required\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eUse Cases\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eAI Inference, Deep Learning, Virtual Desktops, HPC Edge Computing\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eSupported APIs\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eCUDA, cuDNN, TensorRT, DirectX 12, OpenGL 4.6, Vulkan\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eOperating Temperature\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e0°C – 55°C (typical)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003chr\u003e\n\u003ch3\u003e\u003cstrong\u003e❓ Frequently Asked Questions (FAQs)\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp\u003e\u003cstrong\u003eQ1: What are the main workloads supported by the NVIDIA Tesla T4?\u003c\/strong\u003e\u003cbr\u003eA1: The T4 is optimized for AI inference, deep learning, data analytics, and virtual desktop infrastructure (VDI).\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eQ2: Can the T4 GPU be used in a standard server chassis?\u003c\/strong\u003e\u003cbr\u003eA2: Yes. Its low-profile PCIe design fits easily into standard and high-density rack servers.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eQ3: Does the T4 require active cooling?\u003c\/strong\u003e\u003cbr\u003eA3: It’s passively cooled by server airflow, though active-cooled versions exist depending on OEM design.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eQ4: How does the T4 compare to the A100 or A30 GPUs?\u003c\/strong\u003e\u003cbr\u003eA4: The Tesla T4 is optimized for inference and virtualization - offering excellent efficiency at lower power, while A100\/A30 target high-end training and HPC workloads.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eQ5: Are all listed part numbers identical in performance?\u003c\/strong\u003e\u003cbr\u003eA5: Yes - all listed part numbers (900-2G183-0000-001, P09571-001, R0W29C, 490-BFHN, 490-BFLB, UCSC-GPU-T4-16) share the same T4 GPU architecture, memory, and capabilities.\u003c\/p\u003e","brand":"NVIDIA","offers":[{"title":"Default Title","offer_id":46731775475873,"sku":"T4-Nvidia-Tesla-16GB","price":14250.0,"currency_code":"BRL","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/2216\/8673\/files\/NVIDIA-Tesla-T4-16GB-GDDR6-GPU-AI-Inference-Virtualization-Deep-Learning-Accelerator.jpg?v=1784705557","url":"https:\/\/www.foxti.com.br\/products\/nvidia-tesla-t4-16gb-gddr6-gpu-ai-inference-virtualization-deep-learning-accelerator","provider":"FoxTI","version":"1.0","type":"link"}