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Model Architecture Diagram

Community
BBuf
model-architecture-diagram

Return public original model architecture diagrams for user-specified LLM, VLM, MoE, diffusion, OCR, and SGLang/sgl-cookbook model families. Use when the user asks for a model structure chart, architecture diagram, or rendered image link for a specific model such as DeepSeek, GLM, Qwen, Kimi, MiniMax, Step, Hunyuan, or Qwen3-VL.

Overview

PublisherBBuf
RepositoryAI-Infra-Auto-Driven-SKILLS
Skill namemodel-architecture-diagram
Stars
946
Forks
83
Bundled files
3
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by BBuf on GitHub. Read the source before you install it.

Installation

Install the Model Architecture Diagram AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/BBuf/AI-Infra-Auto-Driven-SKILLS/tree/main/skills/model-architecture-diagram
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/BBuf/AI-Infra-Auto-Driven-SKILLS.git /tmp/AI-Infra-Auto-Driven-SKILLS
mkdir -p .claude/skills
cp -r /tmp/AI-Infra-Auto-Driven-SKILLS/skills/model-architecture-diagram .claude/skills/model-architecture-diagram
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Model Architecture Diagram in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Model Architecture Diagram on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Model Architecture Diagram is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Model Architecture Diagram

Workflow

Return only public original diagrams indexed by this skill.

  1. Run the bundled resolver:
bash
python3 skills/model-architecture-diagram/scripts/model_architecture_diagram.py "<model name>"
  1. If the resolver returns kind: existing, return the raw image Markdown it prints and preserve the source attribution line.
  2. If the resolver returns kind: no_match, tell the user that no public original architecture diagram is indexed for that model.

Source Priority

Use references/diagram-index.json as the source of truth. It stores raw GitHub image URLs and official vendor/CDN or pinned Hugging Face resolve/<sha> URLs. Official sources include Qwen and XiaomiMiMo; GitHub sources:

  • datawhalechina/self-llm
  • CalvinXKY/InfraTech
  • Tongyi-MAI/Z-Image
  • Wan-Video/Wan2.1
  • Wan-Video/Wan2.2
  • Tencent-Hunyuan/HunyuanVideo
  • Tencent-Hunyuan/Hunyuan3D-2
  • brayevalerien/Flux.1-Architecture-Diagram

Prefer detailed implementation, cookbook, or architecture-card diagrams over paper figures. Good sources show module boundaries, dataflow, MoE / attention / cache paths, or model-specific runtime structure rather than only a high-level paper overview. Official repository diagrams and curated implementation diagrams are first choice; paper figures are fallback only when no more detailed public original diagram is indexed.

Do not copy remote image binaries into the skill. Return the indexed original URLs so the chat renderer can display the original image.

Existing Diagram Rule

For a direct match, show the original image. Good direct matches include:

  • DeepSeek V3/V3.2/V4, GLM-5, Kimi K2/K2.5/K3, MiniMax M2.5, Qwen3.5, Qwen3-VL, and Step 3.5 Flash from InfraTech.
  • Qwen3.8-Flash-Next has an official diagram (also named qwen4_exp in runtime code). Plain Qwen3.8 2.4T remains no_match; these are different architectures.
  • MiMo V2.6, MiMo V2.5 Pro and GLM-5.2 have indexed originals. GLM-5.3 remains no_match because no direct diagram was verified.
  • Hunyuan-A13B, Kimi-VL, Qwen3, Qwen3-VL detail flows, MiniMax M2, and Llama 4 architecture/module diagrams from self-llm.
  • Z-Image, Wan2.1, Wan2.2, HunyuanVideo, Hunyuan3D 2.0, and FLUX.1 diffusion architecture/module diagrams from public GitHub sources.

If multiple diagrams match, show all high-confidence matches up to the resolver's default limit. For example, DeepSeek V3 may return the full architecture plus MLA MHA/MQA diagrams.

Hosted Original Diagram Gallery

Do not commit the sgl-cookbook-model-architecture-images/ gallery into the repository. The public-original image set is hosted as a GitHub Release asset and indexed by a GitHub issue.

Current hosted artifact:

The gallery is a 2026-05-02 snapshot containing 44 public original diagram image files; it does not mirror the current index, plus a lightweight index.html, index.md, manifest.json, HTML contact sheet, and architecture-audit.md.

To inspect the gallery locally:

bash
curl -L -o /tmp/sgl-cookbook-model-architecture-images-2026-05-02.zip \
  https://github.com/BBuf/AI-Infra-Auto-Driven-SKILLS/releases/download/sgl-cookbook-architecture-images-2026-05-02/sgl-cookbook-model-architecture-images-2026-05-02.zip
unzip -q /tmp/sgl-cookbook-model-architecture-images-2026-05-02.zip -d /tmp
open /tmp/sgl-cookbook-model-architecture-images/index.html

Useful Commands

List known original diagram aliases:

bash
python3 skills/model-architecture-diagram/scripts/model_architecture_diagram.py --list-known

Emit JSON for automation:

bash
python3 skills/model-architecture-diagram/scripts/model_architecture_diagram.py "GLM-5" --format json

References

  • references/diagram-index.json: original diagram link index and aliases.
  • references/source-notes.md: audited source repositories and local cache paths.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Model Architecture Diagram AI skill do?

Return public original model architecture diagrams for user-specified LLM, VLM, MoE, diffusion, OCR, and SGLang/sgl-cookbook model families. Use when the user asks for a model structure chart, architecture diagram, or rendered image link for a specific model such as DeepSeek, GLM, Qwen, Kimi, MiniMax, Step, Hunyuan, or Qwen3-VL.

Why use Model Architecture Diagram on TypingMind?

Because you install it once and use it with any model. Model Architecture Diagram is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Model Architecture Diagram in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/BBuf/AI-Infra-Auto-Driven-SKILLS/tree/main/skills/model-architecture-diagram. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Model Architecture Diagram?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Model Architecture Diagram?

As many as you like. As long as a model supports skills, you can use Model Architecture Diagram with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Model Architecture Diagram AI skill free?

It is published on GitHub by BBuf. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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