Runtime Requirements#

  • NVIDIA Nsight Compute from CUDA Toolkit 13.3 Update 1 or later: nsight-python uses the NVIDIA Nsight Compute CLI (ncu 2026.2.1+). Ensure ncu is installed and available on the system path. The installed ncu-report package must be at least as new (by major and minor version) as this NVIDIA Nsight Compute.

  • NVIDIA CUPTI: The CUPTI backend requires the CUPTI Library from CUDA 13.4 or greater. Installing Nsight Python with the cupti extra (see Installing from PyPI) installs nvidia-cuda-cupti, which provides this library. See CUPTI Compatibility and Requirements for driver compatibility and other setup requirements.

Import Ordering#

import nsight must come before:

  • CUDA initialization: You must import nsight before any operation that initializes CUDA (e.g. torch.cuda.init()). If CUDA is initialized first, NVIDIA Nsight Compute cannot attach correctly and profiling fails (commonly with NV_INJ_ERROR_NOT_INITIALIZED).

    Recommendation: Place import nsight at the top of your script, before all CUDA-related imports and calls.

    This ordering matters because import nsight activates NVIDIA Nsight Compute; see Tools.

  • Any NVTX API calls: nsight-python updates NVTX_INJECTION64_PATH at import time. Any NVTX usage before import nsight will cause NVTX annotation ranges to be missed and profiling results to be incomplete.

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