How Do Content Creators Use DeepMind's Generative Media?

How do I create consistent characters across an entire illustrated project?

Character consistency is the most common challenge in AI-generated media, and the DeepMind framework has a specific solution: reference image injection.

Start by generating one dedicated reference image per character using Nano Banana 2. For complex characters, generate multiple angles — front, back, and side views. These become your character bible.

For every subsequent scene image, pass only the specific reference images for characters appearing in that scene. Do not pass your entire character library — this confuses the model. Do not rely on long-context memory to maintain consistency — it's unreliable for visual details.

This approach works because Nano Banana 2 uses the reference images as direct visual grounding, not just textual description. Your characters will maintain consistent features, clothing, and proportions across dozens or hundreds of generated images.

How do I turn a written story into illustrated multimedia content?

The full pipeline uses Gemini as an orchestrator across all generation models:

1. Upload your source text to a Gemini chat session using the File Upload API. Upload once — chat mode retains context across all subsequent steps.

2. Extract characters: Use structured outputs to get a JSON list of character descriptions and image prompts.

3. Generate reference images: Create character reference images via Nano Banana 2 using Gemini's optimized prompts.

4. Generate scene illustrations: For each chapter/scene, have Gemini produce an image prompt tagged with which characters appear. Pass only those characters' reference images to Nano Banana 2.

5. Generate video: Pass each scene illustration as the starting frame to VO3.1 Light with a Gemini-generated motion description (not the same prompt used for the image — describe what happens after the frame).

6. Generate music: Use Gemini to write audio prompts describing mood, instrumentation, and tempo per chapter. Pass these to LIA 3.

7. Generate narration: Have Gemini rewrite dialogue as a play-style transcript with inline voice style cues. Pass to the TTS model with a 'Read this:' prefix.

Using structured outputs at each step ensures every Gemini response is parseable and can be programmatically routed to the correct downstream model.

What's the difference between image prompts and video motion prompts?

This is a critical distinction many creators miss. An image generation prompt describes a static scene: composition, lighting, characters, setting. A video motion prompt describes what happens after the starting frame: camera movements, character actions, environmental changes.

Reusing your image prompt for video generation produces static or incoherent results. Always generate a separate motion-specific description. Gemini excels at this because it's trained on the same data as VO — it knows what motion descriptions produce the best video output.

For example:

- Image prompt: "A knight standing at the edge of a cliff overlooking a misty valley, golden hour lighting, epic fantasy style"

- Motion prompt: "The camera slowly pushes forward as the knight draws their sword and turns to face the viewer, wind blowing their cape, mist swirling below"

How do I create multi-voice narration without multiple voice IDs?

The TTS model can differentiate voices from inline style cues within a single voice ID. Have Gemini rewrite your text as a play-style transcript:

```

Narrator (warm, measured pace): The forest grew quiet.

Elara (young, British accent, excited): Did you hear that?

Thorne (deep voice, slow, gravelly): Stay behind me.

```

Reuse the same style tag for recurring characters throughout the transcript. Always prefix the full transcript with a read instruction like 'Read this story aloud:' — without this prefix, the TTS model will ignore your text entirely.

Next step: Upload a chapter of your current project to AI Studio, start a Gemini chat session, and ask it to generate character descriptions and image prompts using structured outputs. Generate your first reference images with Nano Banana 2 and see the consistency difference immediately.