Official agent skill

Nemotron Speech

Routes NVIDIA Nemotron Speech (Formerly Riva) NIM tasks — deploys, runs, and tests ASR, TTS, and NMT NIMs on build.nvidia.com or self-hosted.

OfficialApache-2.0Auto-check: notesMedia & Creative

Install Nemotron Speech

skills CLI

$ npx skills add NVIDIA/skills --skill nemotron-speech -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install NVIDIA/skills nemotron-speech --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/nemotron-speech .claude/skills/nemotron-speech && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "nemotron-speech" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nemotron-speech into .claude/skills/nemotron-speech/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-speech", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/NVIDIA/skills/tree/main/skills/nemotron-speech

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add NVIDIA/skills --skill nemotron-speech -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install NVIDIA/skills nemotron-speech --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/nemotron-speech .agents/skills/nemotron-speech && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "nemotron-speech" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nemotron-speech into .agents/skills/nemotron-speech/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-speech", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add NVIDIA/skills --skill nemotron-speech -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install NVIDIA/skills nemotron-speech --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/nemotron-speech .cursor/skills/nemotron-speech && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "nemotron-speech" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nemotron-speech into .cursor/skills/nemotron-speech/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-speech", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/NVIDIA/skills.git --path skills/nemotron-speech

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add NVIDIA/skills --skill nemotron-speech -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install NVIDIA/skills nemotron-speech --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/nemotron-speech .gemini/skills/nemotron-speech && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "nemotron-speech" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nemotron-speech into .gemini/skills/nemotron-speech/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-speech", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install NVIDIA/skills nemotron-speech

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add NVIDIA/skills --skill nemotron-speech -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/nemotron-speech .github/skills/nemotron-speech && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "nemotron-speech" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nemotron-speech into .github/skills/nemotron-speech/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-speech", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add NVIDIA/skills --skill nemotron-speech -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install NVIDIA/skills nemotron-speech --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/nemotron-speech .opencode/skills/nemotron-speech && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "nemotron-speech" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nemotron-speech into .opencode/skills/nemotron-speech/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-speech", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: nemotron-speech
GitHub stars: 3.5k
Token cost: ~3k tokens
SKILL.md length: 1,049 words
Files: 18 (incl. scripts, references)
Skills in repo: 380
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Routes NVIDIA Nemotron Speech (Formerly Riva) NIM tasks — deploys, runs, and tests ASR, TTS, and NMT NIMs on build.nvidia.com or self-hosted.

Tasks that involve Speech recognition and synthesis
SKILL.md covers Purpose, When to Use This Skill, Workflow and Prerequisites, plus 7 more sections
Runs Python scripts from its folder; calls pip and docker; reaches build.nvidia.com; needs NVIDIA_API_KEY and NGC_API_KEY
Tasks that involve Text to speech and voice

What it does

Nemotron Speech is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Routes NVIDIA Nemotron Speech (Formerly Riva) NIM tasks — deploys, runs, and tests ASR, TTS, and NMT NIMs on build.nvidia.com or self-hosted.

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 20 other files, including scripts and reference files (for example `BENCHMARK.md`, `evals/EVAL.md` and `evals/evals.json`).

It sits in Media & Creative, covering Speech recognition and synthesis and Text to speech and voice. It works with NVIDIA AI Platform and Docker. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.

When your agent uses it

Tasks that involve Speech recognition and synthesis
Tasks that involve Text to speech and voice

Example prompts

“Use the nemotron-speech skill to route NVIDIA Nemotron Speech (Formerly Riva) NIM tasks — deploys, runs, and tests ASR, TTS, and NMT NIMs on…”
“/nemotron-speech”

Requirements

Python 3
Docker
A credential in NVIDIA_API_KEY
A credential in NGC_API_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit 67a13c0. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- pip
- docker
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- build.nvidia.com
Also links to:
- docs.nvidia.com
- catalog.ngc.nvidia.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- NVIDIA_API_KEY
- NGC_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Nemotron Speech loads about 3k tokens when it runs, and up to ~47k if it reads all its reference files. Until then it costs about 39 tokens; SKILL.md has 1,049 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~39
When it runs · the whole SKILL.md, loaded when a task matches: ~3k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~47k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NoteRuns commands with sudoSKILL.md:102

nternally), not just the host user. Run `sudo chown 1000:1000 $LOCAL_NIM_CACHE` after creating the directory so the cont

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from NVIDIA/skills at commit 67a13c0, republished under its Apache-2.0 licence (© NVIDIA). 1,049 words, ~2,977 tokens.

Download SKILL.mdSave it as .claude/skills/nemotron-speech/SKILL.md (or your agent's skills folder). This skill also uses 17 other files; get the full folder from GitHub.

name: nemotron-speech
description: Routes NVIDIA Nemotron Speech (Formerly Riva) NIM tasks — deploys, runs, and tests ASR, TTS, and NMT NIMs on build.nvidia.com or self-hosted.
triggers: Nemotron Speech, deploy Riva NIM, deploy ASR/TTS/NMT NIM, Riva ASR, Riva TTS, Riva translation, Parakeet, Canary, Whisper, Nemotron ASR Streaming, Magpie TTS…
version: 1.0.0
license: Apache-2.0
metadata.author: Nemotron Speech Team
metadata.team: riva
metadata.tags: nvidia, nemotron-speech, riva, nim, asr, tts, nmt, speech, speech-to-text, text-to-speech, translation, parakeet, canary, whisper, magpie, nemotron, grpc…
metadata.domain: ml

Nemotron Speech Skills

Note: "Nemotron Speech" is the public-facing name for what NVIDIA documents today as Riva / Riva NIM. All commands, container images, gRPC APIs, Python imports, and documentation URLs still use "Riva" — the rename is brand-only. Do not rename commands, images, or doc URLs.

Agent: When walking the user through a multi-step workflow, announce each step before presenting it: Step N/M — Step Title (e.g., "Step 1/4 — Deploy the Container").

Purpose

Single entry point for all NVIDIA Nemotron Speech (Riva) NIM workflows: ASR (speech-to-text), TTS (text-to-speech), and NMT (translation). Covers cloud-hosted inference via build.nvidia.com, self-hosted Docker deployment, client-protocol choice for ASR (gRPC, HTTP, WebSocket), custom NeMo model deployment via riva-build, ASR pipeline tuning (VAD, diarization, language models), and the prerequisite Docker / NGC / driver setup.

When to Use This Skill

Use this skill for any Nemotron Speech / Riva NIM task — deployment, testing, custom model build, system requirements check, or model selection across ASR / TTS / NMT modalities.

Workflow

Identify the user's task type, then load the corresponding reference file from references/. The reference files contain the detailed per-workflow content; this SKILL.md is a routing surface. Load only the reference relevant to the task at hand.

Prerequisites

For self-hosted deployment: NVIDIA AI Enterprise (NVAIE) entitlement, then complete the environment setup — NVIDIA drivers, Docker, Container Toolkit, NGC API key, Riva Python client. See references/setup.md.
For cloud-hosted inference: pip install -U nvidia-riva-client and a valid NVIDIA_API_KEY from https://build.nvidia.com.
Treat NVIDIA_API_KEY and NGC_API_KEY as secrets: never print, paste, commit, or log real key values. Prefer --password-stdin for Docker login and store persistent keys in a credential manager or a chmod 600 env file rather than world-readable shell startup files.
For self-hosted Docker model caching: host directories mounted at /opt/nim/.cache must be writable by the container user (the NIM container runs as nvs:1000 internally), not just the host user. Run sudo chown 1000:1000 $LOCAL_NIM_CACHE after creating the directory so the container can write to it. Avoid world-writable modes — they let any local user replace cached model artifacts. Also avoid -u "$(id -u):$(id -g)" on the docker run — /opt/nim/workspace inside the container isn't writable to arbitrary UIDs. If you see I/O error Permission denied (os error 13) during model download, the host directory ownership is the issue.

Instructions

Match the user's task to one reference file and load only that file; the references are detailed, so progressive disclosure keeps context tight.
Route setup requests for drivers, Docker, Container Toolkit, and NGC to references/setup.md.
Route GPU compatibility, deployment readiness, and container health checks to references/deployment-readiness-checks.md.
Route model choice across ASR, TTS, and NMT to references/model-selection.md.
Route ASR deployment or inference for Parakeet, Canary, Whisper, and Nemotron ASR Streaming to references/asr.md.
Route custom-trained NeMo ASR deployment (.nemo → RMIR → NIM) to references/asr-custom.md.
Route ASR pipeline configuration for VAD, diarization, language models, and chunk size to references/pipelines.md.
Route TTS deployment or inference for Magpie to references/tts.md.
Route custom or fine-tuned TTS model deployment (.nemo → RMIR → NIM) to references/tts-custom.md.
Route TTS synthesis pipeline configuration — SSML, zero-shot voice cloning, applying an existing pronunciation dictionary, audio encoding, sample rate, custom_configuration keys — to references/tts-pipelines.md. (For discovering and constructing the pronunciation itself, use tts-pronunciation.md.)
Route TTS pronunciation discovery — finding, testing, and applying IPA pronunciations for specific words or phrases — to references/tts-pronunciation.md.
Route NMT deployment or inference for Riva Translate, language pairs, and DNT tags to references/nmt.md.

Source of truth

For per-release detail — current model catalog, container IDs, function IDs, voice lists, VRAM minimums, per-model feature support — fetch or open the canonical NVIDIA doc rather than relying on text in this SKILL.md or the references. Each reference file includes its own routing table to the relevant doc pages.

Top-level landing pages:

Topic	URL
ASR support matrix	https://docs.nvidia.com/nim/speech/latest/reference/support-matrix/asr.html
TTS support matrix	https://docs.nvidia.com/nim/speech/latest/reference/support-matrix/tts.html
NMT support matrix	https://docs.nvidia.com/nim/speech/latest/reference/support-matrix/nmt.html
Prerequisites (driver / GPU / OS)	https://docs.nvidia.com/nim/speech/latest/get-started/prerequisites.html
ASR pipeline configuration	https://docs.nvidia.com/nim/speech/latest/asr/customization/pipeline-configuration.html
ASR runtime customization	https://docs.nvidia.com/nim/speech/latest/asr/customization/customization.html
TTS custom deployment (`.nemo` / `.riva`, `riva-build`, RMIR)	https://docs.nvidia.com/nim/speech/latest/tts/custom-deployment.html
TTS request-time customization (SSML, pronunciation dictionaries, `custom_configuration`)	https://docs.nvidia.com/nim/speech/latest/tts/customization.html
TTS voices and emotional styles	https://docs.nvidia.com/nim/speech/latest/tts/voices.html
TTS zero-shot voice cloning	https://docs.nvidia.com/nim/speech/latest/tts/voice-cloning.html
TTS IPA phone set	https://docs.nvidia.com/nim/speech/latest/tts/phoneme-support.html
Cloud function IDs (per model)	`https://build.nvidia.com/<org>/<model>/api`
NGC model catalog	https://catalog.ngc.nvidia.com/models

Show full SKILL.md (377 more words)Show less

Examples

"Deploy a Parakeet ASR NIM" → load references/asr.md, follow Option B (self-hosted), Steps 1–4.

"Synthesize speech with Magpie" → load references/tts.md, follow Option A (cloud) or Option B (self-hosted).

"Translate English to German" → load references/nmt.md, follow the 4-step flow.

"Convert my fine-tuned .nemo to a NIM" → load references/asr-custom.md for the 4-phase pipeline and references/pipelines.md for build-time config.

"Deploy a custom fine-tuned TTS voice as a NIM" → load references/tts-custom.md for the 4-phase pipeline.

"Use zero-shot voice cloning with Magpie" → load references/tts-pipelines.md.

"Add SSML emphasis tags to my TTS request" → load references/tts-pipelines.md.

"'NVIDIA' sounds wrong in my Magpie TTS output — suggest a few IPA options to test" → load references/tts-pronunciation.md, generate IPA candidates, synthesize variants, then output all three delivery formats.

"How do I fix the pronunciation of 'NIM' in Riva TTS with a custom_dictionary in gRPC Python?" → load references/tts-pronunciation.md, propose IPA for 'NIM', show wire format and gRPC snippet.

"Can my GPU run this?" → load references/deployment-readiness-checks.md and run the 6-step system check.

"Which Riva model should I use?" → load references/model-selection.md, apply the decision framework, then fetch the support matrix for the specific current model name.

Naming & Terminology

Skill brand: Nemotron Speech (public-facing name).
Internal naming preserved: commands (riva-build, riva-deploy, riva_streaming_asr_client), Python client (riva.client), gRPC namespace (nvidia.riva.asr.*), container registry (nvcr.io/nim/nvidia/*), and all NVIDIA documentation URLs still use "Riva". Do not rename these in code, commands, or docs.

Troubleshooting

For task-specific runtime or modality issues, use the relevant reference file (references/<task>.md). Cross-cutting readiness checks:

Container does not become ready → references/deployment-readiness-checks.md (system check + health check table)
Health check fails → references/deployment-readiness-checks.md
docker pull from nvcr.io returns 403 → references/setup.md (Step 5 — Docker login)
Wrong base image / model architecture mismatch → references/asr-custom.md (Phase 2 base image)
VRAM / GPU compatibility → references/deployment-readiness-checks.md, then verify on the support matrix

Limitations

x86_64 architecture only — WSL2 on Windows requires Podman and supports a subset of NIMs (see references/setup.md)
Self-hosted deployment requires an NVIDIA AI Enterprise license
Cloud-hosted inference requires an active NVIDIA_API_KEY and internet access
Public skill branding is "Nemotron Speech"; commands, container images, Python imports (riva.client), gRPC services (nvidia.riva.*), and NVIDIA documentation URLs still use "Riva" — follow official docs and catalogs for naming, do not rename these in commands or code

Next Steps

Verify hardware compatibility: references/deployment-readiness-checks.md
Set up the environment: references/setup.md
Pick a model: references/model-selection.md
Deploy: references/asr.md, references/tts.md, or references/nmt.md

Files

SKILL.md and 17 other files (scripts, references) in skills/nemotron-speech of NVIDIA/skills.

SKILL.md
BENCHMARK.md
evals/EVAL.md
evals/evals.json
references/asr-custom.md
references/asr.md
references/deployment-readiness-checks.md
references/model-selection.md
references/nmt.md
references/pipelines.md
references/setup.md
references/tts-custom.md
references/tts-pipelines.md
references/tts-pronunciation.md
references/tts.md
scripts/main.py
skill-card.md
skill.oms.sig

Open the folder on GitHubat commit 67a13c0

Compare with similar skills

Nemotron Speech next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Nemotron Speech compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Nemotron Speech this skillNVIDIA/skills	3.5k	—	~3k	Automated safety check: Notes	Apache-2.0	yesterday
Nemomajiayu000/claude-skill-registry	666	1 repos	~1.5k	Automated safety check: Pass	Apache-2.0	yesterday
9Router Speech-to-Textdecolua/9router	30k	—	~745	Automated safety check: Pass	MIT	7 days ago
Dotty Av TestBrettKinny/dotty-stackchan	113	—	~866	Automated safety check: Notes	MIT	2 days ago
Local AI Useamd/skills	398	—	~5k	Automated safety check: Notes	MIT	yesterday
Arkcli Code Examplevolcengine/ark-cli	140	—	~743	Automated safety check: Pass	Apache-2.0	9 days ago

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Works with

Questions about Nemotron Speech

What does Nemotron Speech do?

Routes NVIDIA Nemotron Speech (Formerly Riva) NIM tasks — deploys, runs, and tests ASR, TTS, and NMT NIMs on build.nvidia.com or self-hosted. Nemotron Speech is an agent skill from NVIDIA/skills, published by the product's own GitHub organization.com or self-hosted.

When should I use Nemotron Speech?

Nemotron Speech fits situations like: tasks that involve Speech recognition and synthesis; tasks that involve Text to speech and voice.

How do I install Nemotron Speech in Claude Code?

Run `npx skills add NVIDIA/skills --skill nemotron-speech -a claude-code`. Or copy the skill folder (skills/nemotron-speech in NVIDIA/skills) into .claude/skills/nemotron-speech in your project. Claude Code loads it when a task matches its description.

How do I install Nemotron Speech in Codex?

Run `npx skills add NVIDIA/skills --skill nemotron-speech -a codex`. Or copy the skill folder (skills/nemotron-speech in NVIDIA/skills) into .agents/skills/nemotron-speech in your project. Codex loads it when a task matches its description.

Can I use Nemotron Speech in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill nemotron-speech -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nemotron-speech, .gemini/skills/nemotron-speech, .github/skills/nemotron-speech and .opencode/skills/nemotron-speech in your project.

What does Nemotron Speech need to run?

Going by SKILL.md and its folder, Nemotron Speech needs Python for the scripts in its folder, the command-line tools its instructions call (pip and docker) and credentials named NVIDIA_API_KEY and NGC_API_KEY. Our summary lists: Python 3; Docker; A credential in NVIDIA_API_KEY; A credential in NGC_API_KEY.

Does Nemotron Speech access the network?

SKILL.md names 3 domains. In commands or code: build.nvidia.com; the agent is likely to contact it when it follows the instructions. As links in the text: docs.nvidia.com and catalog.ngc.nvidia.com. This is read from the text; nothing was executed.

Is Nemotron Speech safe to install?

Our automated static check of SKILL.md found notes only (runs commands with sudo), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Nemotron Speech use?

Nemotron Speech is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Nemotron Speech use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 44k tokens, read only when the agent opens those files.

What are the alternatives to Nemotron Speech?

Skills that share tags, products or a category with Nemotron Speech: Nemo (majiayu000/claude-skill-registry, 666 stars), 9Router Speech-to-Text (decolua/9router, 30k stars), Dotty Av Test (BrettKinny/dotty-stackchan, 113 stars) and Local AI Use (amd/skills, 398 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Nemotron Speech?

NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,539 GitHub stars. The repository holds 380 skills in this directory. The repository was last updated on October 7, 2026.

Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Nemotron Speech

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

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Safety

SKILL.md

Nemotron Speech Skills

Purpose

When to Use This Skill

Workflow

Prerequisites

Instructions

Source of truth

Examples

Naming & Terminology

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