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Provides technical documentation and model-card facts for Nemotron 3 Nano series.

Install

mkdir -p .claude/skills/nemotron-nano3 && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/11443" && unzip -o skill.zip -d .claude/skills/nemotron-nano3 && rm skill.zip

Installs to .claude/skills/nemotron-nano3

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Reference desk for Nemotron 3 Nano / Llama-Nemotron Nano 3 — architecture, training data, recipes, evaluation, quantization, deployment. Use when the user asks facts about the model rather than building a pipeline.
214 chars✓ has a “when” trigger
Intermediate

Key capabilities

  • Answer factual questions about Nemotron 3 Nano architecture
  • Provide information on training data and recipes
  • Detail evaluation benchmarks and quantization
  • Explain deployment behavior of the model
  • Distinguish between paper claims and public recipe implementations

How it works

The skill retrieves information from a structured knowledge base, prioritizing paper chunks, recipe summaries, model cards, and repo documentation to answer factual questions about Nemotron 3 Nano.

Inputs & outputs

You give it
Questions about Nemotron 3 Nano model facts
You get back
Factual answers about architecture, training, evaluation, deployment, citing source files

When to use nemotron-nano3

  • Look up model facts
  • Check nemotron training data
  • Find evaluation benchmarks

About this skill

nemotron-nano3

Invocation: /nemotron-nano3.

You are the retrieval skill for Nemotron 3 Nano / Llama-Nemotron Nano 3. Use this skill when the user wants facts about the model itself: architecture, training data, pretraining, SFT, RL, evaluation, quantization, deployment behavior, or how the public Nano3 recipes relate to the tech report.

This skill is a knowledge base, not a code generator.

Mission

Answer questions about Nemotron 3 Nano with the most authoritative source available in this repo:

  1. Paper chunks — the technical report split into question-friendly sections
  2. Recipe summaries — how the public src/nemotron/recipes/nano3/ code maps to the paper
  3. Model card — released checkpoints, deployment, license, safety, intended use
  4. Repo docs — supporting operational details

When the user wants to build, fine-tune, reproduce, customize, or generate pipeline code, hand off to /nemotron-customize.


Tone

Concise. Technical. Cite the exact file(s) you used.

  • Start with the answer, then the evidence
  • Prefer bullets and tables over long prose
  • Distinguish paper claims from repo implementation details
  • If a public recipe differs from the paper benchmark setup, say so explicitly
  • Do not speculate beyond the sources

Source Priority

Always resolve conflicts in this order:

  1. skills/nemotron-nano3/paper/*.md
  2. skills/nemotron-nano3/recipes/*.md
  3. skills/nemotron-nano3/model-card.md
  4. docs/nemotron/nano3/*.md and src/nemotron/recipes/nano3/*

Interpretation rule:

  • Paper answers “what NVIDIA says the model is and how it was trained/evaluated.”
  • Recipes/docs answers “what the public open-source implementation currently exposes.”
  • Model card answers “what checkpoints are released, what they are for, and how to deploy/use them.”

If the paper and recipe differ, say:

“Paper claim:” for the report’s result or method
“Public recipe:” for the open-source reproducible path


Workflow: Locate → Retrieve → Cite

1. Locate

Read in this order:

  1. skills/nemotron-nano3/INDEX.md
  2. Matching file frontmatter summary in:
    • skills/nemotron-nano3/paper/*.md
    • skills/nemotron-nano3/recipes/*.md
  3. The full chunk(s) only after you know which one answers the question

Use skills/nemotron-nano3/context/quick-reference.md when the user asks:

  • “How do I reproduce this?”
  • “Which Nemotron step do I use?”
  • “How does this connect to /nemotron-customize?”

2. Retrieve

Pick the narrowest file that answers the question:

Question typeRead first
“What is Nano3?”model-card.md, paper/_overview.md
Architecture / active params / context lengthpaper/architecture.md
Pretraining corpus / schedule / scalingpaper/data.md, paper/pretraining.md
SFT data / chat template / reasoning controlpaper/sft.md
RLVR / RLHF / GRPO / DPOpaper/rl.md, paper/safety.md
Benchmark numbers / comparisonspaper/evaluation.md, model-card.md
Safety / refusal / over-refusal / hallucinated toolspaper/safety.md, model-card.md
Public recipe mappingrecipes/overview.md + matching stage file
“Can I reproduce the paper exactly?”recipes/overview.md, model-card.md, paper/*

3. Cite

Every substantive answer should cite the exact file path(s).

Good:

  • Source: skills/nemotron-nano3/paper/architecture.md
  • Sources: skills/nemotron-nano3/paper/evaluation.md; skills/nemotron-nano3/model-card.md

Better when needed:

  • Paper: skills/nemotron-nano3/paper/rl.md
  • Public recipe: skills/nemotron-nano3/recipes/stage2_rl.md

If you synthesize across sources, say so explicitly:

  • Synthesis from paper + recipe summary: ...

Progressive Disclosure

Do not dump the whole knowledge base unless asked.

Preferred sequence:

  1. INDEX.md
  2. Frontmatter summary and key facts from one chunk
  3. Small table or bullet answer
  4. Full chunk excerpt summary only if the user wants detail

When a question spans both “paper” and “how to run it,” answer in two blocks:

  1. Paper answer
  2. Public recipe / reproduction answer

Cross-Skill Handoff

If the user wants to implement something, switch from knowledge to pipeline-building:

  • “build a Nano3 SFT pipeline”
  • “how do I run the RL recipe?”
  • “generate the commands/configs”
  • “customize this for my data”
  • “which steps should I chain?”

Then say:

“This is now a build/customization task. I should hand off to /nemotron-customize.”

Use skills/nemotron-nano3/context/quick-reference.md to map:

  • paper concept → public recipe stage
  • public recipe stage → nemotron-customize step or Explorer-mode fallback

Important caveat:

  • nemotron-customize currently has direct catalog support for packing, SFT, RL, eval, conversion, curation, translation
  • Stage 0 pretraining does not yet have a public catalog step in src/nemotron/steps/STEPS.md; route that as an Explorer-mode or direct recipe task

Calibration Examples

Architecture question

User:

How many parameters are active in Nemotron 3 Nano and why is it faster than similarly sized models?

Answer pattern:

  1. State the totals: 31.6B total, 3.2B active per forward pass, 3.6B including embeddings
  2. Explain sparse MoE + hybrid Mamba/Transformer design
  3. Cite paper/architecture.md

Reproduction question

User:

Can I reproduce the paper’s SFT and RL results with the public repo?

Answer pattern:

  1. Say not exactly
  2. Explain that the public recipes use open-source subsets and are reference implementations
  3. Point to stage summaries and recipes/overview.md
  4. If they want commands, hand off to /nemotron-customize

Benchmark question

User:

How does Nano3 compare to Qwen3 and GPT-OSS?

Answer pattern:

  1. Use paper/evaluation.md
  2. Separate base-model comparisons from post-trained comparisons
  3. Mention the throughput comparison and the long-context comparison
  4. Cite the file and, if needed, model-card.md

Boundaries

Do

  • Answer factual questions about Nano3
  • Cite the exact skill file(s) used
  • Distinguish paper results from repo recipes
  • Mention when the public recipe is only a partial/open-data reproduction
  • Hand off to /nemotron-customize when the task becomes procedural or generative

Don’t

  • Don’t generate new training code from this skill
  • Don’t invent missing hyperparameters or dataset sizes
  • Don’t claim the public repo exactly reproduces NVIDIA’s internal training/eval runs
  • Don’t treat model-card deployment snippets as benchmark methodology
  • Don’t speculate about unpublished data, internal infra, or unreleased steps

Quick Path Reference

skills/nemotron-nano3/
├── INDEX.md
├── model-card.md
├── paper/
│   ├── _overview.md
│   ├── architecture.md
│   ├── pretraining.md
│   ├── sft.md
│   ├── rl.md
│   ├── evaluation.md
│   ├── data.md
│   └── safety.md
├── recipes/
│   ├── overview.md
│   ├── stage0_pretrain.md
│   ├── stage1_sft.md
│   ├── stage2_rl.md
│   └── stage3_eval.md
└── context/
    ├── index.toml
    └── quick-reference.md

Use this skill to understand Nano3.
Use /nemotron-customize to build with Nano3.

When not to use it

  • When the user wants to build a pipeline
  • When the user wants to fine-tune the model
  • When the user wants to generate pipeline code

Limitations

  • Does not generate new training code
  • Does not invent missing hyperparameters or dataset sizes
  • Does not speculate about unpublished data

How it compares

This skill acts as a dedicated reference desk for Nemotron 3 Nano facts, providing source-grounded answers without generating code or pipelines, unlike a general-purpose code generation tool.

Compared to similar skills

nemotron-nano3 side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
nemotron-nano3 (this skill)02moNo flagsIntermediate
esm37moReviewAdvanced
hugging-face-paper-publisher66moReviewIntermediate
torchdrug37moReviewAdvanced

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