---
id: pynvvideocodec
version: "2.2.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# pynvvideocodec — pynvvideocodec (PyNvVideoCodec) is NVIDIA's Python library for hardware-accelerated video encode/decode on NVIDIA GPUs.

License: permissive · Maintenance: active · Downloads: 700.4K/mo

## What it is and what it does

PyNvVideoCodec is NVIDIA's official Python library for offloading video encode, decode, and transcode operations to NVIDIA GPUs. It wraps the Video Codec SDK and exposes a Python API for hardware-accelerated video processing, eliminating CPU bottlenecks in video pipelines. The library supports decoding from H.264, HEVC, AV1, VP8, VP9, VC1, MPEG4, MPEG2, and MPEG1 streams, with flexible frame access modes (sequential, random, batched, sliced) and output to multiple formats including NV12, YUV420, YUV444, and RGB24. Encoding supports H.264, HEVC, and AV1 codecs from various input formats.

The package is designed for high-throughput video processing on data centers (DGX Spark) and edge devices (Jetson), with features like multi-GPU decode/encode, in-memory video processing from Python byte buffers, threaded decoding with near-zero latency, and segment-based transcoding. It handles GIL contention in multithreaded scenarios and extracts low-level decode statistics (QP values, motion vectors) from H.264 and H.265 streams.

Use it for:

- Decode video files or streams on GPU for real-time computer vision pipelines without CPU overhead.
- Transcode video segments by timestamp range for content editing or partial processing workflows.
- Process video directly from memory buffers (S3, network streams) without writing temporary files.
- Extract decode statistics and SEI metadata from H.264/H.265 streams for quality analysis.
- Build multi-GPU video processing pipelines on Jetson or DGX systems for edge AI applications.

## Worth the install?

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

PyNvVideoCodec provides hardware-accelerated video encoding, decoding, and transcoding on NVIDIA GPUs through Python APIs, supporting multiple codecs and output formats.

Yes, if you have an NVIDIA GPU and need to encode, decode, or transcode video in Python. The package is actively maintained, MIT-licensed, has no Python runtime dependencies, and is officially supported by NVIDIA. Medium install friction is acceptable given the GPU-specific nature. Verify that your GPU and drivers meet the Video Codec SDK requirements before installing.

## Install

pip install pynvvideocodec
uv add pynvvideocodec
poetry add pynvvideocodec

## Installing pynvvideocodec

Before you install: Medium install friction due to platform-specific wheels (x86_64, aarch64, Windows) and likely GPU driver dependencies. Actively maintained with a recent release (17 days old). No runtime Python dependencies to manage.

License in practice: MIT license permits commercial and private use with minimal restrictions—you may use, modify, and distribute the package freely provided you include the license notice.

Quickstart:

pip install pynvvideocodec

import pynvvideocodec
# Decode a video file
decoder = pynvvideocodec.PyNvDecoder(input_file='video.mp4')
frame = decoder[0]  # Fetch first frame

Requires an NVIDIA GPU with Video Codec SDK support and appropriate GPU drivers installed; Python 3.8 or later.

Verify before relying:

- Whether specific NVIDIA GPU models or compute capabilities are required for encode/decode operations.
- Whether the package requires NVIDIA Video Codec SDK to be separately installed on the system.
- Performance characteristics and throughput for typical video resolutions and codecs.
- Compatibility with specific versions of NVIDIA drivers.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 700.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

nvidia gpu video encoding, hardware accelerated video decode, gpu video transcoding python, nvidia video codec sdk python, gpu accelerated video processing, gpu-accelerated, video-codec, nvidia-official

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