vss-benchmark-vlm-qa skillB
vss-benchmark-vlm-qa is agent-read markdown (skill) from nvidia-ai-blueprints/video-search-and-summarization: Benchmark video Q&A accuracy and latency of a deployed RT-VLM (Cosmos Reason 3) via vss vlm run, using questions and videos from the DSS vss-devx-base dataset. Replaces the deprecated nat eval / vss-agent QA path. Not for tool-calling or trajectory evaluation, and not for LVS summarization throughput..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Benchmark video Q&A via `vss vlm` Measure **accuracy** (LLM-as-judge vs ground truth) and **latency** of end-to-end video question answering by calling **`vss vlm run`** against a deployed Cosmos Reason 3 RT-VLM. Questions and clips come from DSS dataset **`vss-devx-base`** (`nvdataset`). This replaces `docker exec vss-agent nat eval` for the QA slice. It does **not** score tool-calling or trajectories. ## When to use - The user asks to benchmark / evaluate VLM video Q&A after vss-agent / NAT eval was removed. - The user wants latency and answer accuracy on `vss-devx-base`. ## When not to use - Tool-calling or trajectory evaluation — out of scope. - LVS summarization throughput — use `vss-benchmark-video-summarization`. - Ad-hoc single questions — use `/vss-ask-video`. ## Prerequisites - A VSS stack with RT-VLM serving Cosmos Reason 3, and `vss configure` already run so `vss configure check` lists `rt_vlm` as `ok` and `vst` as `ok`. **Configure with a routable address, not `localhost`.** Clips are addressed as VIOS sensors so RT-VLM fetches them by URL; the URL VIOS mints is built from the …
Read the whole file at its exact version.
How to install
mdr add nvidia-ai-blueprints/video-search-and-summarization/vss-benchmark-vlm-qa@v3.3.0mdr add nvidia-ai-blueprints/video-search-and-summarization/vss-benchmark-vlm-qa@sha256:5157780ec73b76dfPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_umytbeeqk2yswbwv)
1 badge views in 30 days
Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v3.3.0 latest | 2026-09-23 | 71f6e8b | 10,173 B | B | view · diff |
| v3.3.0 | 2026-09-19 | d672ffc | 8,876 B | B | view |
Audit of the latest version
- fail: No link to a raw IP address (matched: http://127.0.0.1:8000)
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (10173 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No script tag
Source
nvidia-ai-blueprints/video-search-and-summarization · 1,876 stars · license NOASSERTION · pushed 2026-09-24 · branch develop
API
GET https://markdownregistry.com/api/v1/artifacts/art_umytbeeqk2yswbwv GET https://markdownregistry.com/api/v1/resolve?ref=nvidia-ai-blueprints/video-search-and-summarization/vss-benchmark-vlm-qa GET https://markdownregistry.com/api/v1/blob/5157780ec73b76dfd97eaf1b855691f5def33ad37a0308b7ff2d6bfba29c6f1f
Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
More from nvidia-ai-blueprints/video-search-and-summarization
Every file in nvidia-ai-blueprints/video-search-and-summarization