How Gemini Omni Handles Multiple Reference Inputs

Gemini Omni accepts any combination of text, images, video, and audio as inputs, then merges them into a single cohesive video output. You don't pick one input type and commit to it — you stack references in a chat conversation and describe how they should combine. This works best when each reference has a clear job: one for character, one for style, one for setting, and text to direct the action.

What "Reference Anything" Actually Means

The site's core claim is that you can "turn any reference — image, text, video, or audio — into a single, cohesive output." In practice, that means the model treats each input as a constraint or guide rather than a separate generation task. The output is one video, not four.

The interface reflects this: a text field for describing "the video scene, camera motion and dynamic actions," plus a reference asset slot with a 0/5000 character budget, and a single Generate Video action.

Multi-Image Fusion

Multi-Image Fusion is the named feature for combining several images into one output. This is the mechanism behind character and scene consistency — instead of describing a character in words and hoping the model reproduces them, you supply the image directly and let the fusion step carry that identity into the generated video.

A practical use: give one image of a character, one image of a location, and a text prompt describing what happens. The fusion step keeps the character recognizable while placing them in the referenced setting.

How References Guide Consistency

Gemini Omni's stated strength is character and scene consistency across shots. References do the heavy lifting here:

• Character consistency — a reference image anchors facial features and clothing so they survive camera moves and scene changes.
• Scene consistency — a location image or video clip keeps background, lighting, and layout stable.
• Style consistency — a reference image can carry a visual treatment (color grade, art style) across the whole output.

Because everything runs through natural conversation, you can correct drift mid-project. If a character's appearance shifts, you re-supply the reference and describe the fix rather than rebuilding the prompt from scratch.

Practical Multimodal Prompting

A workable pattern for combining inputs:

1. Assign one job per reference. Don't give three images that all try to define the character — split roles (character, setting, style).
2. Write text that references the assets explicitly. Describe the scene, camera motion, and actions, and make clear which asset governs what.
3. Generate, then adjust conversationally. Use follow-ups like changing the background to night or adding a camera zoom instead of rewriting everything.
4. Use Remix for variations. The Remix feature produces instant variations of an existing video from a simple text prompt — useful once a base composition works.

For example, a task might be: fuse a portrait photo (character), a street photo (setting), and a text prompt specifying a slow dolly-in at dusk. If the result drifts, re-anchor with the same references and a narrower instruction.

What to Watch For

• The reference asset field is capped at 5000 characters, so text direction is bounded — keep prompts focused.
• The site advertises a free trial and a separate pricing page; check the pricing page for current terms rather than assuming limits.
• Multi-Image Fusion and chat-based editing are the two features doing most of the multimodal work — if consistency matters, lean on fusion rather than pure text description.