> This page is for version 9.2 (default).
> For other versions, use one of these documentation indexes:
> - 9.2 (default): https://docs.nvidia.com/deepstream/9.2/llms.txt
> - Archives: https://docs.nvidia.com/deepstream/archives/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/deepstream/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/deepstream/_mcp/server.

# FAQ for DeepStream GitHub Mono-repo

## 1. Where is the DeepStream GitHub mono-repo located?

[https://github.com/NVIDIA/DeepStream](https://github.com/NVIDIA/DeepStream)

Starting with DeepStream 9.0, this mono-repo is the unified home for DeepStream source, samples, tools, and skills across x86, Jetson, and SBSA. SDK release packages moved to the mono-repo GitHub release assets in DeepStream 9.1 (see Q3).

## 2. Where can I download the DeepStream SDK packages?

Starting from DeepStream 9.1, all DeepStream SDK packages are available as release assets on the NVIDIA DeepStream GitHub mono-repo:

[https://github.com/NVIDIA/DeepStream/releases/tag/v9.1.0](https://github.com/NVIDIA/DeepStream/releases/tag/v9.1.0)

Navigate to the release corresponding to your DeepStream version and download the required package from the **Assets** section.

## 3. Why has DeepStream moved to GitHub for release packages?

The [NVIDIA/DeepStream](https://github.com/NVIDIA/DeepStream) GitHub mono-repo is the unified platform for all DeepStream releases. DeepStream 9.0 introduced the mono-repo as the release channel. Starting from DeepStream 9.1, the mono-repo GitHub releases page is the single place for both the release and all downloadable SDK packages.

## 4. What packages are available in the DeepStream 9.2 GitHub release assets?

DeepStream 9.2 packages are available from the **Assets** section of the
[DeepStream 9.2 release](https://github.com/NVIDIA/DeepStream/releases/tag/v9.2.0).

* **Full SDK tarballs**
  * `deepstream_sdk_v9.2.0_x86_64.tbz2` — x86 dGPU
  * `deepstream_sdk_v9.2.0_jetson.tbz2` — Jetson
  * `deepstream_sdk_v9.2.0_sbsa.tbz2` — ARM SBSA/DGX Spark
* **Full SDK Debian packages**
  * `deepstream-9.2_9.2.0-1_amd64.deb` — x86 dGPU
  * `deepstream-9.2_9.2.0-1_arm64.deb` — Jetson
* **Binary-only packages** — `deepstream-binaries-x86` and
  `deepstream-binaries-aarch64`, available as tarballs and Debian packages
* **Sample data package** — `deepstream-sample-data`, available as a tarball
  and Debian package
* **DeepStream Libraries wheel** — Python wheel for x86

## 5. What is the difference between the full DeepStream package and the deepstream-binaries package?

* **Full DeepStream package**: Contains the complete SDK — all open-source components and proprietary libraries — for users who want to install DeepStream directly.
* **deepstream-binaries package**: Contains only the proprietary binary libraries. This is intended for users who build DeepStream from source using the mono-repo and need only the closed-source components to complement their build.

### Components open sourced with DeepStream 9.2

The following components are open source starting with DeepStream 9.2.
Architecture columns identify the corresponding runtime files.

> **Note**
>
> Open-source availability does not imply current support, a recommendation to
> use the component, or a stable public API. Refer to the component documentation
> and repository license files for support and licensing details.

#### GStreamer plugins

| File/component                | x86      | aarch64  |
| ----------------------------- | -------- | -------- |
| `libnvdsgst_visionencoder.so` | Included | Included |
| `gst-nvdstextembedder`        | Included | Included |
| `libgstnvunixfd.so`           | Included | NA       |
| `libgstnvvideo4linux2.so`     | Included | NA       |

#### Libraries

| File/component                             | x86      | aarch64  |
| ------------------------------------------ | -------- | -------- |
| `libnvds_3d_alignment_datafilter.so`       | Included | Included |
| `libnvds_3d_common.so`                     | Included | Included |
| `libnvds_3d_dataloader_realsense.so`       | Included | Included |
| `libnvds_3d_depth2point_datafilter.so`     | Included | Included |
| `libnvds_3d_depth_datasource.so`           | Included | Included |
| `libnvds_3d_gl_datarender.so`              | Included | Included |
| `libnvds_3d_gles_ensemble_render.so`       | Included | Included |
| `libnvds_3d_glprocess.so`                  | Included | Included |
| `libnvds_3d_multisensor_mixer.so`          | Included | Included |
| `libnvds_3d_sensor_fusion_cluster.so`      | Included | Included |
| `libnvds_3d_video_databridge.so`           | Included | Included |
| `libnvds_csvparser.so`                     | Included | Included |
| `libnvds_custom_sequence_preprocess.so`    | Included | Included |
| `libnvds_dsanalytics.so`                   | Included | Included |
| `libnvds_infercustomparser.so`             | Included | Included |
| `libnvds_inferutils.so`                    | Included | Included |
| `libnvds_lidar_custom_postprocess_impl.so` | Included | Included |
| `libnvds_lidar_custom_preprocess_impl.so`  | Included | Included |
| `libnvds_lidarfilewrite.so`                | Included | Included |
| `libnvds_tritoninferfilter.so`             | Included | Included |
| `libnvdsgst_3d_gst.so`                     | Included | Included |
| `libnvdsgst_helper.so`                     | Included | Included |
| `libnvdsgst_tensor.so`                     | Included | Included |
| `libnvdsgst_sparse4d.so`                   | Included | Included |
| `libnvv4l2.so`                             | Included | NA       |
| `libnvv4lconvert.so`                       | Included | NA       |
| `libnvds_batch_jpegenc.so`                 | Included | Included |

**NA** means **Not applicable** for that architecture.

## 6. Where can I find the NVIDIA-AI-IOT GitHub repositories in the GitHub mono-repo?

The table below maps the existing NVIDIA-AI-IOT GitHub repository sources to their location within the GitHub mono-repo:

| NVIDIA-AI-IOT GitHub repo                                                                             | Location within the GitHub mono-repo                                                                                 |
| ----------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------- |
| [NVIDIA-AI-IOT/deepstream_tao_apps](https://github.com/NVIDIA-AI-IOT/deepstream_tao_apps)             | [NVIDIA/DeepStream/src/apps/tao_apps/](https://github.com/NVIDIA/DeepStream/tree/main/src/apps/tao_apps)             |
| [NVIDIA-AI-IOT/deepstream_reference_apps](https://github.com/NVIDIA-AI-IOT/deepstream_reference_apps) | [NVIDIA/DeepStream/src/apps/reference_apps/](https://github.com/NVIDIA/DeepStream/tree/main/src/apps/reference_apps) |
| [NVIDIA-AI-IOT/deepstream_tools](https://github.com/NVIDIA-AI-IOT/deepstream_tools)                   | [NVIDIA/DeepStream/tools/](https://github.com/NVIDIA/DeepStream/tree/main/tools)                                     |
| [NVIDIA-AI-IOT/DeepStream_Coding_Agent](https://github.com/NVIDIA-AI-IOT/DeepStream_Coding_Agent)     | [NVIDIA/DeepStream/skills/](https://github.com/NVIDIA/DeepStream/tree/main/skills)                                   |
| [NVIDIA-AI-IOT/inference_builder](https://github.com/NVIDIA-AI-IOT/inference_builder)                 | [NVIDIA/DeepStream/tools/inference_builder/](https://github.com/NVIDIA/DeepStream/tree/main/tools)                   |
| [NVIDIA-AI-IOT/auto-magic-calib](https://github.com/NVIDIA-AI-IOT/auto-magic-calib)                   | [NVIDIA/DeepStream/tools/auto-magic-calib/](https://github.com/NVIDIA/DeepStream/tree/main/tools)                    |
| [NVIDIA-AI-IOT/deepstream_dockers](https://github.com/NVIDIA-AI-IOT/deepstream_dockers)               | [NVIDIA/DeepStream/deepstream_dockers/](https://github.com/NVIDIA/DeepStream/tree/main/deepstream_dockers)           |
| [NVIDIA-AI-IOT/deepstream_libraries](https://github.com/NVIDIA-AI-IOT/deepstream_libraries)           | [NVIDIA/DeepStream/deepstream_libraries/](https://github.com/NVIDIA/DeepStream)                                      |

## 7. Where do I get the DeepStream Libraries Python wheel?

Starting with DeepStream 9.1, the DeepStream Libraries Python wheel is published as a release asset on the mono-repo GitHub releases page, alongside the other SDK packages:

[https://github.com/NVIDIA/DeepStream/releases/tag/v9.1.0](https://github.com/NVIDIA/DeepStream/releases/tag/v9.1.0)

Download the wheel (for example `deepstream_libraries-1.4-cp312-cp312-linux_x86_64.whl`) from the **Assets** section and install it with `pip3 install <wheel>`. The DeepStream Libraries source and sample applications are hosted as part of the mono-repo at [https://github.com/NVIDIA/DeepStream](https://github.com/NVIDIA/DeepStream). See [DeepStream Libraries](/text/DS_Libraries) for full setup and usage details.

## 8. How do I download DeepStream release assets from GitHub using wget or curl?

You can download release assets directly from the command line using `curl` or `wget`.

**Using curl:**

```bash
$ curl -LO 'https://github.com/NVIDIA/DeepStream/releases/download/v9.2.0/deepstream-9.2_9.2.0-1_amd64.deb'
```

**Using wget:**

```bash
$ wget --content-disposition 'https://github.com/NVIDIA/DeepStream/releases/download/v9.2.0/deepstream-9.2_9.2.0-1_amd64.deb'
```

Replace the filename with the specific asset you want to download from the release page.

## 9. Where can I download DeepStream SDK packages and container images?

Starting from DeepStream 9.1, all SDK packages are available through the GitHub releases page at [https://github.com/NVIDIA/DeepStream/releases/tag/v9.1.0](https://github.com/NVIDIA/DeepStream/releases/tag/v9.1.0).

DeepStream Docker container images are distributed through [ghcr.io/nvidia/deepstream](https://ghcr.io/nvidia/deepstream).

## 10. Where are the DS 9.1 public tar/deb files?

They are now located in the DeepStream mono-repo. See the DS 9.1 release tag:

[https://github.com/NVIDIA/DeepStream/releases/tag/v9.1.0](https://github.com/NVIDIA/DeepStream/releases/tag/v9.1.0)

## 11. Where are current Jetson DeepStream containers published?

The legacy `deepstream-l4t` container repository will not be updated in future DeepStream releases, though old releases remain accessible to users.

Current Jetson and dGPU container images are distributed through [ghcr.io/nvidia/deepstream](https://ghcr.io/nvidia/deepstream).

## 12. Where did the DeepStream Open Source Dockers move to for DS 9.1? (previously [https://github.com/NVIDIA-AI-IOT/deepstream_dockers](https://github.com/NVIDIA-AI-IOT/deepstream_dockers))

[https://github.com/NVIDIA/DeepStream](https://github.com/NVIDIA/DeepStream)

## 13. Where are DeepStream Skills, auto-magic-calib, and inference-builder located with GitHub Monorepo?

These repos are now also hosted into the mono-repo as listed below:

* **DeepStream Skills**: [https://github.com/NVIDIA/DeepStream/tree/main/skills](https://github.com/NVIDIA/DeepStream/tree/main/skills)
* **auto-magic-calib** (Original repo [https://github.com/NVIDIA-AI-IOT/auto-magic-calib](https://github.com/NVIDIA-AI-IOT/auto-magic-calib)): [https://github.com/NVIDIA/DeepStream/tree/main/tools](https://github.com/NVIDIA/DeepStream/tree/main/tools)
* **inference-builder** (Original repo [https://github.com/NVIDIA-AI-IOT/inference_builder](https://github.com/NVIDIA-AI-IOT/inference_builder)): [https://github.com/NVIDIA/DeepStream/tree/main/tools](https://github.com/NVIDIA/DeepStream/tree/main/tools)

## 14. Are there any proprietary files in the DeepStream mono-repo?

Yes, please refer to the EULA file packaged within the proprietary tar/deb released as
[GitHub Release assets](https://github.com/NVIDIA/DeepStream/releases/tag/v9.2.0).

> **Note**
>
> The open-source components in the mono-repo are licensed under the
> [Apache License 2.0](https://github.com/NVIDIA/DeepStream/blob/main/LICENSE).

## 15. I am observing a warning while launching dockers: "groups: cannot find name for group ID 993" or similar. Where does this come from?

This is just a warning. It was introduced in `nvidia-container-toolkit` 1.19.1-1. For more details, see:

[https://github.com/cncf-tags/container-device-interface/issues/175](https://github.com/cncf-tags/container-device-interface/issues/175)

This applies to all platforms (x86/Jetson/SBSA).

## 16. How do I build or modify DeepStream components on SBSA / DGX Spark?

Starting with DeepStream 9.2, the SBSA/DGX Spark SDK tarball
`deepstream_sdk_v9.2.0_sbsa.tbz2` is published in the
[DeepStream 9.2 release assets](https://github.com/NVIDIA/DeepStream/releases/tag/v9.2.0).

You can also use the official Docker container, which ships with DeepStream fully installed and all dependencies pre-configured:

[https://ghcr.io/nvidia/deepstream](https://ghcr.io/nvidia/deepstream)

To modify a specific open-source component inside the container, clone the mono-repo and run `make` only in that component's directory. Since all prerequisites are already present in the container, there is no need to run the full `build/build.sh`:

```bash
$ git clone https://github.com/NVIDIA/DeepStream.git
$ cd DeepStream/src/<component-directory>
$ make && sudo make install
```