QUICKSPECS

  • 6144 CUDA Cores
  • 192 3rd Gen Tensor Cores
  • 48 2nd Gen RT Cores
  • 20 GB memory (GDDR6)
  • 70W Power Consumption
  • 4x Mini DP 1.4a
  • Category:
    General Details

    NVIDIA RTX 4000 SFF ADA

    PERFORMANCE FOR ENDLESS POSSIBILITIES.

    The NVIDIA RTX™ 4000 SFF Ada Generation packs a punch with the features, capabilities, and performance demanded by professionals—all in a compact GPU design. Powered by the NVIDIA Ada Lovelace architecture, the RTX 4000 SFF is a compact powerhouse, combining third-gen RT Cores, fourth-gen Tensor Cores, and next-gen CUDA® cores with 20GB of graphics memory for excellent rendering, AI, graphics, and compute workload performance.

    NVIDIA RTX professional graphics cards are certified with a broad range of professional applications, tested by leading independent software vendors (ISVs) and workstation manufacturers, and backed by a global team of support specialists. Get the peace of mind needed to focus on what matters with the premier visual computing solution for mission-critical business

    POWERED BY THE NVIDIA AMPERE ARCHITECTURE


    NVIDIA ADA Architecture CUDA

    2X the speed of the previous generation for single-precision floating-point (FP32) operations provides significant performance improvements for graphics and simulation workflows on the desktop, such as complex 3D computer-aided design (CAD) and computer-aided engineering (CAE).


    Third-Generation RT Cores

    With up to 2X the throughput over the previous generation, third-generation RT Cores deliver massive speedups for workloads like photorealistic rendering of movie content, architectural design evaluations, and virtual prototyping of product designs. This technology also accelerates the rendering of ray-traced motion blur with greater visual accuracy.


    4rd-Gen Tensor Cores

    Fourth-generation Tensor Cores deliver more than 2X the AI performance of the previous generation. These Tensor Cores support acceleration of the FP8 precision data type and provide independent floating-point and integer data paths to speed up execution of mixed floating-point and integer calculations.


    20GB of GPU Memory

    With 20GB GDDR6 memory, RTX 4000 SFF gives designers, engineers, and creative professionals the large memory needed to work with large models, datasets, and workloads like rendering, product design, and simulation.


    AV1 Encoders

    Eighth-generation dedicated hardware encoder (NVENC) with AV1 encoding unlocks new opportunities for streamers, broadcasters, and video conferencing. It’s 40% more efficient than H.264, allowing users streaming at 1080p to increase their resolution to 1440p while running at the same bit rate and quality.

    Specifications

    Technical details NVIDIA RTX 4000 SFF ADA

    1. CUDA Cores
      NVIDIA Ada Lovelace architecture-based CUDA Cores 6144
    2. Tensor Cores
      NVIDIA forth-generation Tensor Cores 192
    3. RT Cores
      NVIDIA third-generation RT Cores 48
    4. Memory
      GPU memory 20 GB GDDR6
    5. Single-precision Performance
      Single-precision performance 19.2 TFLOPS
    6. RT Core performance
      RT Core performance 44.3 TFLOPS
    7. Tensor performance
      Tensor performance 306.8 TFLOPS
    8. Max Power Consumption
      Power Consumption Total Board power: 70 W
    9. Graphics Bus
      System interface PCI Express 4.0 x 16
    10. Display Connectors
      Display Connectors 4x Mini DisplayPort 1.4a
    11. Form Factor
      Form Factor 2.7″ (H) x 6.6″ Dual Slot
    12. Form Factor
      Max simultaneous displays 4x 4096 x 2160 @ 120 Hz,
      4x 5120 x 2880 @ 60 Hz,
      2x 7680 x 4320 @ 60 Hz
    13. Display Connectors
      vGPU software support No
    14. Tensor Cores
      Encode/decode engines 2x encode, 2x decode (+AV1 encode and decode)
    15. VR Ready
      VR Ready Yes
    16. Form Factor
      Graphics APIs DirectX 12
      Shader Model 6.6
      OpenGL 4.6
      Vulkan 1.3
    17. Single-precision performance
      Compute APIs CUDA 11.6
      DirectCompute
      OpenCL 3.0
    18.  

     

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