jetson-video-benchmark
jetson-video-benchmark is an agent skill published by nvidia, listed under writing code. It lives in the NVIDIA/skills repository, which has 3,735 GitHub stars and is licensed under Apache-2.0; we last read it on 2026-09-25.
Measures encode/decode throughput for Jetson Video Codec SDK or PyNvVideoCodec, comparing presets or surfaces, testing codec-worker capacity with authenticated samples and user media, and produces documentation-derived planning estimates when representative media is unavailable. Also supports video requests limited to PSNR or SSIM.
Install
skills is a generic installer for any repository of Claude agent skills -- it reads NVIDIA/skills’s own structure rather than assuming one, the same way this page reads the skill’s own SKILL.md rather than assuming a format.
npx skills add NVIDIA/skills
Maintenance
Use when measuring Jetson Video Codec SDK or PyNvVideoCodec encode/decode throughput, comparing presets or surfaces, testing codec-worker capacity with authenticated samples and user media, or producing a clearly labeled documentation-derived planning estimate when representative media is absent. Also use for a video request limited to PSNR or SSIM, to apply the terminal scope response.
jetson-video-benchmark compared with similar skills
| Skill | Publisher | What it does | Repo stars | Last update |
|---|---|---|---|---|
| jetson-video-benchmark (this page) | nvidia | Use when measuring Jetson Video Codec SDK or PyNvVideoCodec encode/decode throughput, comparing presets or su… | 3,735 | 2026-10-26 |
| cudaq-importing(same repository) | nvidia | Use when porting circuits from another framework (e.g. Qiskit) into CUDA-Q kernels while preserving the sourc… | 3,735 | 2026-10-26 |
| cuopt-numerical-optimization-api(same repository) | nvidia | LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with an… | 3,735 | 2026-10-26 |
| cuopt-routing-api-python(same repository) | nvidia | Vehicle routing (VRP, TSP, PDP) with cuOpt — Python API only. Use when the user is building or solving routin… | 3,735 | 2026-10-26 |
| cupynumeric-install(same repository) | nvidia | Install and verify cuPyNumeric for Python — requirements, commands, verification. Source builds are out of sc… | 3,735 | 2026-10-26 |
| cupynumeric-migration-readiness(same repository) | nvidia | Pre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins… | 3,735 | 2026-10-26 |
| doca-common(same repository) | nvidia | Use this skill whenever the user is doing hands-on DOCA programming on a BlueField DPU or ConnectX NIC and ne… | 3,735 | 2026-10-26 |
Skills from the same repository first, then others for this job by repository stars. Figures are from each repository when we last read it.
Common questions about jetson-video-benchmark
- What does jetson-video-benchmark do?
- Measures encode/decode throughput for Jetson Video Codec SDK or PyNvVideoCodec, comparing presets or surfaces, testing codec-worker capacity with authenticated samples and user media, and produces documentation-derived planning estimates when representative media is unavailable. Also supports video requests limited to PSNR or SSIM.
- How do I install jetson-video-benchmark?
- Run npx skills add NVIDIA/skills. The skills installer reads the repository’s own structure, so it works for any repository of agent skills.
- Who publishes jetson-video-benchmark?
- nvidia.
- Is jetson-video-benchmark maintained, and what licence does it use?
- Its repository has 3,735 GitHub stars and its state in our directory is listed. Its last commit we recorded was on 2026-10-26. The repository declares the Apache-2.0 licence.
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