TutorialsKnowledge cards: fundamentals & concepts
5 core concepts + 6 categories + 4 use cases + 8 high-frequency scenarios + tool selection — see the lingo, boundaries, and the right tool before making cards.
This lesson only covers "what it is" and "what it can do": 5 core concepts to set boundaries, 6 categories to map card types, 4 use cases to find scenarios, 8 high-frequency scenarios matched to tonight's 7 templates — and finally, picking the right tool: why Qwen Image 3.0 is the best fit for knowledge cards.
5 Core Concepts
6 Categories
These 6 categories are universal — they apply to ancient poems, exams, science popularization, and health tips.
Rote memorization
Rules, policies, concepts, statutes. Example: five social insurances guide, campus recruiting timeline.
Action steps
Methods, processes, operations. Example: 5-step resume submission, interview answering steps.
Example comparison
Right/wrong comparison, template references. Example: good vs bad self-evaluation.
Pitfall warning
Avoid mistakes, landmine warnings. Example: 3 contract signing traps, interview taboos.
Thinking prompt
Inspire thinking, explore positioning, ease mindset. Example: how to judge whether a job fits you.
Script template
Direct language templates. Example: self-introduction template, HR talking points.
4 Use Cases
Prepare for exams, memorize formulas, review concepts — efficient use of fragmented time.
Typical cards: exam-prep card · vocabulary card.
Distill reading / lecture key points, build your personal knowledge base.
Typical cards: reading note card · lecture distillation card.
Course material, micro-lesson assets, simplify complex content.
Typical cards: classroom knowledge-point card · training cheat sheet.
Image-text cards are easy to save and forward — perfect for popular science sharing.
Typical cards: science-pop card · ancient-poem card · recipe card.
8 High-Frequency Scenarios
8 scenarios correspond to tonight's 7 templates — find the scenario closest to yours and use the template directly.
| Scenario | What the job is (lingo) | How AI helps |
|---|---|---|
| Long-text distillation | Compress dozens of pages of handouts / posts into dry goods | One-shot output of key points + golden quotes + cases |
| Image-text knowledge card | One page per knowledge point | Structured prompts generate shareable cards |
| Reading note card | Book excerpts / reviews → visualized cards | Distill core viewpoints + quotes, auto layout |
| Exam-prep card | High-frequency test points + mnemonics | Generate Q&A cards + memory anchors |
| Ancient-poem card | Imagery + recitation + annotations | Generate poetic cards + ink-wash illustrations |
| Workplace skill card | Office tips / industry knowledge / onboarding | Generate quick-reference cards + action steps |
| Science / recipe / atlas cards | A styled series of knowledge cards | Batch production once the style is fixed |
| Quote poster / sharing card | Book quotes → pretty cards worth posting | One-tap layout for Moments / Xiaohongshu |
Pick the Right Tool: Why Qwen Image 3.0
A knowledge card is essentially "the image with the most text" — title, bullet points, quotes, numbers; not a single character can be wrong. So choosing a tool isn't just about "painting pretty", it's about "writing text correctly".
The Text-to-Image Landscape
On "painting pretty", the gap between domestic and global models has closed; on "writing text correctly", the real gap shows — and knowledge cards are exactly the most text-heavy images.
Top models on the global text-to-image leaderboard (Arena · early August 2026):
| Rank | Model | Vendor | Elo | One-line impression |
|---|---|---|---|---|
| 1 | GPT Image 2 | OpenAI | 1380 | Global chart-topper, released April 2026 |
| 2 | MAI-Image-2.6 | Microsoft | 1336 | Enterprise-grade integration |
| 3 | Grok Imagine 2.0 | xAI | 1316 | Most relaxed permissions |
| 4 | Reve 2.1 | Reve | 1302 | Layered generation, strong layout |
| 5 | Muse Image | Meta | 1282 | Meta's new star |
| 8~9 | Qwen Image 3.0 / Seedream 5.0 | Alibaba / ByteDance | 1257~58 | Domestic first tier |
Note: scores vary slightly across leaderboards and dates; GPT Image 2 is the strongest overall, but knowledge cards compete on "text accuracy".
Domestic Models Side by Side
| Model | Vendor | Strengths | Weaknesses |
|---|---|---|---|
| Jimeng / Doubao (Seedream 5.0) | ByteDance | Well-balanced, fast, visually striking, 4K, good ecosystem | Precise text/digits unreliable, rewrites info; some watermarks |
| Qwen Image 3.0 | Alibaba | Leading Chinese text rendering, complex layouts, 4.5k long prompts, cheap | Weights not open-sourced, cloud-only; occasional garbled tiny English |
| Hunyuan Image 3.0 | Tencent | Fully open source, best at anime / 2D characters | Knowledge-card layout isn't its home turf |
| Wenxin Yige / ERNIE | Baidu | Stable Chinese scenarios, good Chinese glyph generation | Conservative styles |
| Kling / Kolors | Kuaishou | Strong video generation, image-to-video, character consistency | Static knowledge cards aren't its home turf |
For knowledge cards — cards full of text — what matters is Chinese comprehension and text accuracy, and in real tests Qwen is the most stable.
Why Qwen Image 3.0
Qwen Image 3.0 (released July 2026 · fully available in August) has a one-word official positioning: "practical" — from "looks good" to "works well".
- Accurate Chinese comprehension, high text accuracy (most critical) — Natively trained on Chinese; tested on the ~800-character "Preface to Tengwang Pavilion" with zero missing/wrong characters; 140 mixed Chinese-English-digit characters with 0 errors; titles/body/dates/percentages mixed without garbling.
- Small text stays legible — Precise 10px small-text rendering; tiny footnotes at the card bottom used to be a disaster zone, now they're readable; formulas, sub/superscripts, and LaTeX also render.
- Swallows whole passages in one shot — Up to 4.5k token input (~1k for the previous generation); the full distilled copy can be fed in at once; one-shot 9-grid explainer / newspaper / exam-paper layouts.
- Cheap and sufficient — Text-to-image from ¥0.18/image (Standard), Pro around ¥0.25~0.5/image; same tier as GPT Image 2 at an order of magnitude lower price.
How to use: Qwen AI platform (chat.qwen.ai) free trial ｜ Alibaba Cloud Bailian API (qwen-image-3.0-pro / -standard)
Image quality decides whether a card "looks good"; text accuracy decides whether it's "fit to post" — Qwen Image 3.0 makes cards "postable".
In the next lesson we dive into the soul of the course — the three-step method: deconstruct → generate → polish, plus 4 tips so AI stops "guessing style".