---
id: nvidia-cufile-cu12
version: "1.14.1.1"
license: LicenseRef-NVIDIA-Proprietary
license_treatment: unclear
maintenance: aging
---

# nvidia-cufile-cu12 — cuFile GPUDirect libraries

License: unclear · Maintenance: aging · Downloads: 14.5M/mo

## What it is and what it does

nvidia-cufile-cu12 is a Python interface to NVIDIA's cuFile library, which implements GPUDirect Storage—a technology that allows GPUs to read and write data directly to storage devices without routing through the CPU. This eliminates a major bottleneck in data-intensive workloads like machine learning training and scientific computing.

The package is designed for CUDA 12 environments and targets developers working with high-performance GPU applications that need fast I/O. It has no Python runtime dependencies, but requires a compatible NVIDIA GPU, CUDA 12 installation, and a Linux system (x86_64 or aarch64). The package is classified as Beta and has not been updated in over a year, suggesting it may not receive active maintenance.

Use it for:

- Accelerate training loops in deep learning frameworks by enabling direct GPU reads from large datasets stored on disk or network storage.
- Speed up scientific simulations that process massive arrays by avoiding CPU memory copies during I/O operations.
- Optimize data pipelines in machine learning inference servers that need to load and process batches with minimal latency.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides Python bindings for NVIDIA's cuFile GPUDirect storage access libraries, enabling direct GPU-to-storage I/O without CPU involvement for CUDA 12 environments.

Yes, if you have a CUDA 12 GPU workload on Linux that is I/O-bound and you need GPUDirect Storage acceleration. No, if you are on Windows, do not have CUDA 12, or your workload is not storage-intensive enough to justify the added complexity. Verify NVIDIA's proprietary license terms and check that your system has the required cuFile runtime before installing.

## Install

pip install nvidia-cufile-cu12
uv add nvidia-cufile-cu12
poetry add nvidia-cufile-cu12

## Installing nvidia-cufile-cu12

Before you install: Medium install friction due to platform-specific wheels (x86_64 and aarch64 Linux only). Package is aging—last release was 435 days ago—with no visible repository or commit history in the fact sheet, making it difficult to assess ongoing maintenance.

License in practice: Licensed under a proprietary NVIDIA license (LicenseRef-NVIDIA-Proprietary) with unclear treatment. Verify NVIDIA's terms before use in commercial or redistributed projects.

Quickstart:

pip install nvidia-cufile-cu12
import cufile
# Use cuFile APIs for GPU-direct storage operations

Requires NVIDIA CUDA 12 and compatible GPU; only x86_64 and aarch64 Linux wheels are available despite Windows classifier listing.

Verify before relying:

- Whether this package requires a local NVIDIA cuFile installation or runtime library on the system
- Compatibility with specific CUDA 12.x versions and whether it works across all CUDA 12 minor releases
- Whether Windows support (listed in classifiers) is actually available given only Linux wheels in friction evidence

## Package facts

- License: LicenseRef-NVIDIA-Proprietary (unclear)
- Python support: supports_current
- Install friction: medium
- Maintenance: aging
- Downloads: 14.5M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

gpu direct storage access, nvidia cufile python, gpudirect i/o cuda, nvidia storage acceleration, cuda gpu storage library, gpu-acceleration, cuda, storage-io

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