How to build NVEnc

• Windows
• Linux (Ubuntu 20.04 - 24.04)
• Linux (Ubuntu 18.04)
• Linux (Fedora 33)

Windows

0. Requirements

To build NVEnc, components below are required.

• Visual Studio 2022
• CUDA 10.1 or later (x64)
• CUDA 11.0 or later (x86)
• Avisynth SDK
• VapourSynth SDK
• [Optional] ONNX Runtime GPU package 1.23 or later (for --vpp-onnx)

1. Install build tools.

Install Avisynth+ and VapourSynth, with the SDKs.

Then, "avisynth_c.h" of the Avisynth+ SDK and "VapourSynth.h" of the VapourSynth SDK should be added to the include path of Visual Studio.

These include path can be passed by environment variables "AVISYNTH_SDK" and "VAPOURSYNTH_SDK".

With default installation, environment variables could be set as below.

setx AVISYNTH_SDK "C:\Program Files (x86)\AviSynth+\FilterSDK"
setx VAPOURSYNTH_SDK "C:\Program Files (x86)\VapourSynth\sdk"

Additionally to build NVEncNVSDKNGX.dll and NVEncNVOFFRUC.dll using "ReleaseNVDLL" config, you will need to download and extract RTX Video SDK and Optical Flow SDK, and then set environment variables "RTX_VIDEO_SDK" and "OPTICAL_FLOW_SDK".

setx RTX_VIDEO_SDK "<...>\RTX_Video_SDK_v1.1.0"
setx OPTICAL_FLOW_SDK "<...>\Optical_Flow_SDK_5.0.7"

To build with --vpp-onnx support, download and extract the GPU package from ONNX Runtime Releases, and set ONNXRUNTIME_DIR to the extracted directory. For example, if onnxruntime-win-x64-gpu-1.23.2.zip is extracted to F:\VisualStudio2022\Projects\onnxruntime, set the environment variable as below.

setx ONNXRUNTIME_DIR "F:\VisualStudio2022\Projects\onnxruntime"

Environment variables set by setx become available to newly started command prompts or Visual Studio instances. Restart Visual Studio if it was already running. When launching a Windows build from WSL, also set WSLENV so the environment variable is passed to Windows processes.

export ONNXRUNTIME_DIR='F:\VisualStudio2022\Projects\onnxruntime'
export WSLENV=ONNXRUNTIME_DIR

At runtime, place onnxruntime.dll and provider DLLs (onnxruntime_providers_cuda.dll, etc.) in %ONNXRUNTIME_DIR%\lib next to NVEncC64.exe, or make them visible through PATH.

2. Download source code

git clone https://github.com/rigaya/NVEnc --recursive
cd NVEnc
curl -s -o ffmpeg_lgpl.7z -L https://github.com/rigaya/ffmpeg_dlls_for_hwenc/releases/download/20250830/ffmpeg_dlls_for_hwenc_20250830.7z
7z x -offmpeg_lgpl -y ffmpeg_lgpl.7z

3. Build NVEncC.exe / NVEnc.auo

Finally, open NVEnc.sln, and start build of NVEnc by Visual Studio.

Linux (Ubuntu 20.04 - 24.04)

0. Requirements

• GPU Driver 435.21 or later
• C++17 Compiler
• meson + ninja-build
• CUDA 10-12
• rust + cargo-c
• git
• libraries
  • ffmpeg 4.x-7.x libs (libavcodec*, libavformat*, libavfilter*, libavutil*, libswresample*, libavdevice*)
  • libass9
  • [Optional] ONNX Runtime GPU package 1.23 or later (for --vpp-onnx)
  • [Optional] AvisynthPlus
  • [Optional] VapourSynth

1. Install build tools

• Install build tools

  sudo apt install build-essential git meson ninja-build
  

• Install rust + cargo-c (for libdovi build)

  sudo apt install libssl-dev curl pkgconf
  curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --profile minimal \
    && . ~/.cargo/env \
    && cargo install cargo-c
  

2. Install NVIDIA driver

3. Install CUDA

Download CUDA deb file for each OS.

# For Ubuntu 20.04
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.1-1_all.deb
# For Ubuntu 22.04
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb

Install CUDA.

sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install --no-install-recommends cuda-toolkit
export CUDA_PATH=/usr/local/cuda

CUDA_VER_MAJOR=12
CUDA_VER_MINOR=4
apt-get -y install cuda-compiler-${CUDA_VER_MAJOR}-${CUDA_VER_MINOR} \
  cuda-cudart-dev-${CUDA_VER_MAJOR}-${CUDA_VER_MINOR} cuda-driver-dev-${CUDA_VER_MAJOR}-${CUDA_VER_MINOR} \
  cuda-nvrtc-dev-${CUDA_VER_MAJOR}-${CUDA_VER_MINOR} libcurand-dev-${CUDA_VER_MAJOR}-${CUDA_VER_MINOR} \
  libnpp-dev-${CUDA_VER_MAJOR}-${CUDA_VER_MINOR} cuda-nvml-dev-${CUDA_VER_MAJOR}-${CUDA_VER_MINOR}

4. Install required libraries

Install ffmpeg and other required libraries.

sudo apt install ffmpeg \
  libavcodec-extra libavcodec-dev libavutil-dev libavformat-dev libswresample-dev libavfilter-dev libavdevice-dev \
  libass-dev libx11-dev libplacebo-dev

5. [Optional] Install AvisynthPlus

AvisynthPlus is required only if you need AvisynthPlus(avs) reader support.

Please go on to [7. Build NVEncC] if you don't need avs reader.

sudo apt install cmake

git clone https://github.com/AviSynth/AviSynthPlus.git
cd AviSynthPlus
mkdir avisynth-build && cd avisynth-build 
cmake ../
make && sudo make install
cd ../..

6. [Optional] Install VapourSynth

VapourSynth is required only if you need VapourSynth(vpy) reader support.

Please go on to [7. Build NVEncC] if you don't need vpy reader.

sudo apt install python3-pip cython3 autoconf automake libtool meson libzimg-dev

git clone https://github.com/vapoursynth/vapoursynth.git
cd vapoursynth
./autogen.sh
./configure
make && sudo make install

# Make sure vapoursynth could be imported from python
# Change "python3.x" depending on your environment
sudo ln -s /usr/local/lib/python3.x/site-packages/vapoursynth.so /usr/lib/python3.x/lib-dynload/vapoursynth.so
sudo ldconfig

LD_LIBRARY_PATH=/usr/local/lib vspipe --version

7. Build NVEncC

git clone https://github.com/rigaya/NVEnc --recursive
cd NVEnc
meson setup ./build --buildtype=release
meson compile -C ./build

For --vpp-onnx support, the build checks ONNX Runtime headers in standard include paths and onnxruntime_dir. If they are not found, the required headers are downloaded automatically into the build directory.

To use an extracted ONNX Runtime package for the headers explicitly, pass it to onnxruntime_dir. For example, if onnxruntime-linux-x64-gpu-1.23.2.tgz is extracted to /opt/onnxruntime-linux-x64-gpu, configure as below.

meson setup ./build --buildtype=release -Donnxruntime_dir=/opt/onnxruntime-linux-x64-gpu
meson compile -C ./build

At runtime, the GPU package from ONNX Runtime Releases is still required. Make /opt/onnxruntime-linux-x64-gpu/lib visible through LD_LIBRARY_PATH or an equivalent library search path.

Check if it works properly.

./build/nvencc --check-hw

You shall get information of the avaliable codecs supported by NVENC.

NVEnc (x64) 7.24 (r2526) by rigaya, Apr 28 2023 14:52:09 (gcc 12.2.0/Linux)
  [NVENC API v12.0, CUDA 12.1]
 reader: raw, y4m, avs, vpy, avsw, avhw [H.264/AVC, H.265/HEVC, MPEG2, VP8, VP9, VC-1, MPEG1, MPEG4, AV1]
#0: NVIDIA GeForce RTX 4080 (9728 cores, 2505 MHz)[2147483.64]
Avaliable Codec(s)
H.264/AVC
H.265/HEVC
AV1

Linux (Ubuntu 18.04)

0. Requirements

• GPU Driver 435.21 or later
• C++17 Compiler
• meson + ninja-build
• CUDA 10
• git
• libraries
  • ffmpeg 4.x libs (libavcodec58, libavformat58, libavfilter7, libavutil56, libswresample3, libavdevice58)
  • libass9
  • [Optional] VapourSynth

1. Install build tools

• Install build tools

  sudo apt install git g++-8 meson ninja-build
  

• Install rust + cargo-c (for libdovi build)

  sudo apt install libssl-dev curl
  curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --profile minimal \
    && . ~/.cargo/env \
    && cargo install cargo-c
  

2. Install NVIDIA driver and CUDA 10.2

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget http://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-2-local-10.2.89-440.33.01/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda
export CUDA_PATH=/usr/local/cuda

After reboot, check if the driver has been installed properly. (Tested on AWS g3s.xlarge)

$ nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01    Driver Version: 440.33.01    CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla M60           On   | 00000000:00:1E.0 Off |                    0 |
| N/A   28C    P8    15W / 150W |      0MiB /  7618MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

3. Install required libraries

Install ffmpeg 4.x libraries.

sudo add-apt-repository ppa:jonathonf/ffmpeg-4
sudo apt update
sudo apt install ffmpeg \
  libavcodec-extra58 libavcodec-dev libavutil56 libavutil-dev libavformat58 libavformat-dev libavdevice58 libavdevice-dev \
  libswresample3 libswresample-dev libavfilter-extra7 libavfilter-dev libass9 libass-dev

4. [Optional] Install VapourSynth

VapourSynth is required only if you need VapourSynth(vpy) reader support.

Please go on to [6. Build NVEncC] if you don't need vpy reader.

sudo apt install python3-pip autoconf automake libtool meson

git clone https://github.com/sekrit-twc/zimg.git --recursive
cd zimg
./autogen.sh
./configure
make && sudo make install
cd ..

sudo pip3 install Cython

git clone https://github.com/vapoursynth/vapoursynth.git
cd vapoursynth
./autogen.sh
./configure
make && sudo make install

# Make sure vapoursynth could be imported from python
# Change "python3.x" depending on your environment
sudo ln -s /usr/local/lib/python3.x/site-packages/vapoursynth.so /usr/lib/python3.x/lib-dynload/vapoursynth.so
sudo ldconfig

vspipe --version

# Install lsmash
git clone https://github.com/l-smash/l-smash.git
cd l-smash
./configure --enable-shared
make && sudo make install
cd ..
 
# Install vslsmashsource
git clone https://github.com/HolyWu/L-SMASH-Works.git
cd L-SMASH-Works/VapourSynth
meson build
cd build
ninja && sudo ninja install
cd ../../../

5. Build NVEncC

git clone https://github.com/rigaya/NVEnc --recursive
cd NVEnc
CXX=g++-8 meson setup ./build --buildtype=release
meson compile -C ./build

Check if it works properly.

./build/nvencc --check-hw

You shall get information of the avaliable codecs supported by NVENC. (Tested on AWS g3s.xlarge)

#0: Tesla M60 (2048 cores, 1177 MHz)[PCIe3x16][440.33]
Avaliable Codec(s)
H.264/AVC
H.265/HEVC

Linux (Fedora 33)

0. Requirements

• C++17 compiler
• meson + ninja-build
• CUDA 11
• git
• libraries
  • ffmpeg 4.x libs (libavcodec58, libavformat58, libavfilter7, libavutil56, libswresample3, libavdevice58)
  • libass9
  • [Option] AvisynthPlus
  • [Option] VapourSynth

1. Install build tools

• Install build tools

  sudo dnf install @development-tools meson ninja-build
  

• Install rust + cargo-c (for libdovi build)

  sudo apt install libssl-dev curl
  curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --profile minimal \
    && . ~/.cargo/env \
    && cargo install cargo-c
  

2. Getting ready to install CUDA and NVIDIA driver

sudo dnf update
sudo dnf upgrade
sudo dnf clean all
sudo dnf install kernel-devel
sudo dnf install make pciutils acpid libglvnd-devel
sudo dnf install dkms

3. Install CUDA and NVIDIA driver

Install CUDA and the NVIDIA driver included in CUDA package.

wget https://developer.download.nvidia.com/compute/cuda/11.2.1/local_installers/cuda-repo-fedora33-11-2-local-11.2.1_460.32.03-1.x86_64.rpm
sudo rpm -ivh cuda-repo-fedora33-11-2-local-11.2.1_460.32.03-1.x86_64.rpm
sudo dnf clean all
sudo dnf install cuda
reboot

CUDA was installed in /usr/local/cuda.

After reboot, check if the driver has been installed properly.

$ nvidia-smi
Sun Mar  7 14:27:45 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 1080    Off  | 00000000:0D:00.0 Off |                  N/A |
|  0%   27C    P8     7W / 230W |     65MiB /  8111MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1335      G   /usr/libexec/Xorg                  56MiB |
|    0   N/A  N/A      1476      G   /usr/bin/gnome-shell                6MiB |
+-----------------------------------------------------------------------------+

4. Install required libraries

Install ffmpeg and other required libraries.

sudo dnf install https://download1.rpmfusion.org/free/fedora/rpmfusion-free-release-$(rpm -E %fedora).noarch.rpm
sudo dnf install ffmpeg ffmpeg-devel libass libass-devel

5. [Optional] Install AvisynthPlus

AvisynthPlus is required only if you need AvisynthPlus(avs) reader support.

Please go on to [7. Build NVEncC] if you don't need avs reader.

sudo dnf install cmake

git clone git://github.com/AviSynth/AviSynthPlus.git
cd AviSynthPlus
mkdir avisynth-build && cd avisynth-build 
cmake ../
make && sudo make install
cd ../..

# Build lsmash
git clone https://github.com/l-smash/l-smash.git
cd l-smash
./configure --enable-shared
make && sudo make install
cd ..

# Build lsmashsource
git clone https://github.com/HolyWu/L-SMASH-Works.git
cd L-SMASH-Works
git checkout -b 20200531 refs/tags/20200531
cd AviSynth
meson build
cd build
ninja && sudo ninja install
cd ../../../

6. [Option] Install VapourSynth

VapourSynth is required only if you need VapourSynth(vpy) reader support.

Please go on to [7. Build NVEncC] if you don't need vpy reader.

sudo dnf install zimg zimg-devel meson autotools automake libtool python3-devel ImageMagick

sudo pip3 install Cython --install-option="--no-cython-compile"

git clone https://github.com/vapoursynth/vapoursynth.git
cd vapoursynth
./autogen.sh
./configure
make && sudo make install

# Make sure vapoursynth could be imported from python
# Change "python3.x" depending on your environment
sudo ln -s /usr/local/lib/python3.x/site-packages/vapoursynth.so /usr/lib/python3.x/lib-dynload/vapoursynth.so
sudo ldconfig

vspipe --version

# Build lsmash (Not required if already done in 5.3)
git clone https://github.com/l-smash/l-smash.git
cd l-smash
./configure --enable-shared
make && sudo make install
cd ..
 
# Build vslsmashsource
git clone https://github.com/HolyWu/L-SMASH-Works.git
cd L-SMASH-Works
git checkout -b 20200531 refs/tags/20200531
cd VapourSynth
meson build
cd build
ninja && sudo ninja install
cd ../../../

7. Build NVEncC

git clone https://github.com/rigaya/NVEnc --recursive
cd NVEnc
meson setup ./build --buildtype=release
meson compile -C ./build

Check if it works properly.

./build/nvencc --check-hw

You shall get information of the avaliable codecs supported by NVENC.

#0: GeForce GTX 1080 (2560 cores, 1822 MHz)[PCIe3x16][460.32]
Avaliable Codec(s)
H.264/AVC
H.265/HEVC