How do I bind reference images to specific roles in the prompt?

Use inline `<IMAGE_REF_0>`, `<IMAGE_REF_1>`, `<IMAGE_REF_2>` tags in your prompt to assign each reference a role. Example: "The character in <IMAGE_REF_0> walks through the setting in <IMAGE_REF_1>, wearing the outfit from <IMAGE_REF_2>." Explicit tags dramatically improve predictability, especially with 3+ references. For alternative multi-ref workflows, compare with <a href="https://www.jaiportal.com/model/seedance-20-reference-to-video">Seedance 2.0 Reference-to-Video</a>.

Google Gemini Omni Flash Reference-to-Video

Google Gemini Omni Flash multi-reference video generation. Combine multiple images + prompt to guide subject, motion, style, and audio in the output. 720p, 3-10s.

"The character in <IMAGE_REF_0> walks through the scenic location in <IMAGE_REF_1>. Smooth camera. Cinematic lighting."

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Describe your scene and generate a video in seconds

8,500+ videos generated this month

📄 About Google Gemini Omni Flash Reference-to-Video

**Google Gemini Omni Flash Reference-to-Video** is the multi-image **reference to video ai** in the Omni Flash family — you upload up to **6 reference images**, describe the scene you want in the prompt, and the model synthesizes a **3–10 second 720p clip with synchronized audio** guided by every reference. It's the fastest way to lock **character consistency**, style transfer, or product-in-scene composition across a video without the drift that plagues single-prompt text-to-video generation. The workflow answers a specific creative problem: **how do you get the exact character, the exact product, the exact style, in the exact environment — all at once**? Single-prompt text-to-video tools force you to describe everything in words, which is fragile and lossy. Reference-to-Video lets you show instead of tell. Character reference in image 0, environment in image 1, outfit in image 2, mood-board style ref in image 3 — the model reads all four and generates a video that respects each. That makes it a **multi image video generator** built for creative teams who need controllable, brand-consistent output. **Explicit reference binding is the power tool.** The prompt supports inline `<IMAGE_REF_0>`, `<IMAGE_REF_1>`, `<IMAGE_REF_2>` tags that bind each image to a specific role. Example prompt: *"The character in <IMAGE_REF_0> walks through the location in <IMAGE_REF_1>, wearing the outfit from <IMAGE_REF_2>. Cinematic golden hour light. Slow dolly forward. Ambient street sound."* Skip the tags and the model still infers roles from image content — but with 3+ references, explicit tagging cuts ambiguity dramatically and produces predictable results. Every generation ships with **synchronized ambient audio** baked into the timeline, same as the other Omni Flash video variants — no separate SFX pass. Motion is grounded in Gemini's physics reasoning, so characters walk with anatomically correct gait, objects fall correctly, hair moves naturally with head rotation. That's the difference between AI video that feels alive and AI video that warps into an uncanny puddle around second 3. **Character consistency use cases are where this model shines.** Feed the same character reference across ten separate scene generations and the model holds identity across all of them — the recipe for **character consistency video** storytelling: episodic content, brand mascot campaigns, serial short-form fiction. Product marketers use it the same way with product references: same watch, same handbag, same bottle, dropped into ten different environments. **Where Reference-to-Video fits in the JAI Portal video stack:** it's the multi-reference workhorse. For simpler animate-a-still workflows, use the sibling <a href="https://www.jaiportal.com/model/gemini-3-pro-image-preview">Omni Flash Image-to-Video</a>. For alternative multi-reference workflows, compare with <a href="https://www.jaiportal.com/model/seedance-20-reference-to-video">Seedance 2.0 Reference-to-Video</a> and <a href="https://www.jaiportal.com/model/wan-2-6-reference-to-video">Wan 2.6 Reference-to-Video</a>. For prompt-only text-to-video generation without references, use <a href="https://www.jaiportal.com/model/veo-3-text-to-video">Veo 3</a> or <a href="https://www.jaiportal.com/model/seedance-20-text-to-video">Seedance 2.0 Text-to-Video</a>. Live pricing across every video model is on the <a href="https://chat.jaiportal.com/model-pricing">JAI Portal model pricing dashboard</a>. Output is **720p in 16:9 or 9:16** at **~$0.13 per second** — a 5-second reference-guided clip is roughly $0.65, an 8-second clip about $1.00. Generation latency runs 30–90 seconds. Every output includes **full commercial-use rights on paid generations** and ships as standard MP4 with audio ready to drop into any platform.

✨ Key Features

**Multi-image reference** — up to 6 images per generation, each guiding subject, environment, style, prop or mood-board direction.

**Explicit reference binding** via `<IMAGE_REF_0>`, `<IMAGE_REF_1>` tags in the prompt for controllable, predictable role assignment.

**Character consistency across scenes** — feed the same character ref into multiple generations to hold identity across an entire episodic series.

**Synchronized audio synthesis** — ambient sound and environmental effects generated in the same pass as the video, no post-production needed.

**Physics-grounded motion** driven by Gemini's world knowledge — natural gait, correct gravity, plausible dynamics across the 3–10s window.

**720p output in 16:9 or 9:16** — sized for YouTube, desktop, TikTok, Reels and Shorts distribution.

**Pay-per-second pricing** at ~$0.13/sec — a 5-second reference-guided clip is roughly $0.65 in credits.

💡 Use Cases

⚡**Serial content creators** producing episodic short-form fiction with a recurring character — same character ref, different scene refs, per episode.

⚡**Brand mascot campaigns** — hold the mascot identity across a whole seasonal ad campaign by reusing the character reference across every generation.

⚡**Product marketers** dropping the same product (watch, handbag, bottle, sneaker) into 10+ distinct environments for social ad rotation.

⚡**Fashion & apparel brands** producing multi-scene lookbook motion clips — same model + different outfit refs + different location refs, all consistent.

⚡**Ad agencies** running creative variants of a hero concept — same subject and style refs, iterating environments and moods for A/B testing.

⚡**Illustrators & animators** stylizing a character reference into cinematic motion clips with a consistent visual identity across an entire series.

⚡**Storyboard artists & pre-viz teams** generating rough motion pre-viz of a scene from reference plates before committing to full production.

🎯 Best For

🎯 {"Character consistency across a multi-clip series or campaign.","Multi-reference composition — subject + environment + style + prop in one prompt.","Product-in-scene motion clips for rotating social ad creative.","Style-transfer video anchored to a mood-board reference.","Brand-consistent short-form video where identity must hold across many clips."}

👍 Pros

✓Up to 6 reference images per generation — deepest multi-ref workflow in the Omni Flash line.

✓Explicit `<IMAGE_REF_N>` binding for predictable role assignment.

✓Character consistency across generations — the foundation of episodic AI video.

✓Synchronized audio baked into every output.

✓Physics-grounded motion holds identity better than single-prompt T2V.

✓16:9 and 9:16 for full-format social distribution.

✓Full commercial-use rights on paid generations.

⚠️ Considerations

△Only 16:9 and 9:16 aspect ratios — no 1:1 or 4:5 formats.

△Beyond 3–4 references, guidance can dilute — quality plateaus.

△Max 10 seconds per generation — long-form work requires stitching.

△Output caps at 720p — for 1080p/4K delivery, upscale after generation.

△Skipping `<IMAGE_REF_N>` tags with 3+ references reduces predictability.

📚 How to Use Google Gemini Omni Flash Reference-to-Video

Upload 2–3 reference images for the strongest results. Reference 0 is usually your character or primary subject. Reference 1 is typically the environment or scene. Reference 2 might be outfit, prop or style mood.

Write your prompt with explicit `<IMAGE_REF_N>` tags: "The character in <IMAGE_REF_0> walks through the location in <IMAGE_REF_1>, wearing the outfit from <IMAGE_REF_2>. Slow dolly forward. Cinematic golden hour."

Include motion direction ("slow dolly forward", "orbit around subject", "static wide") and audio cues ("footsteps on gravel", "soft cafe ambiance") in the same prompt.

Pick aspect ratio and duration — 9:16 for TikTok/Reels/Shorts, 16:9 for YouTube. 5–8 second sweet spot for social hooks. Longer clips increase drift risk.

Generate. Latency runs 30–90 seconds. If the character drifts, tighten the reference binding language: "Preserve exact facial features and body proportions from <IMAGE_REF_0>."

For a serial workflow, save reference 0 and reuse it across all future generations to hold character identity across an episodic series or campaign. Compare motion styles with <a href="https://www.jaiportal.com/model/wan-2-6-reference-to-video">Wan 2.6 Reference-to-Video</a>.

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Frequently Asked Questions

Use inline ``, ``, `` tags in your prompt to assign each reference a role. Example: "The character in walks through the setting in , wearing the outfit from ." Explicit tags dramatically improve predictability, especially with 3+ references. For alternative multi-ref workflows, compare with Seedance 2.0 Reference-to-Video.

**Up to 6 per generation.** 2–3 references usually give the strongest guidance — beyond that, prompt guidance can dilute the subject or style signal. Common recipes: character + environment (2), character + environment + outfit (3), character + environment + outfit + style ref (4). Save your best character reference and reuse it across generations for character consistency.

Yes — synchronized ambient sound and environmental effects are baked into every output, same as the other Omni Flash video variants. Include audio cues in your prompt ("wind through pine", "footsteps on gravel", "soft cafe ambiance") to steer what the model synthesizes on the audio track.

Yes — this is arguably the strongest use case. Save your character reference (or product reference) and reuse it across every generation. The model holds identity remarkably well across serial content, brand mascot campaigns and episodic storytelling. It's the recipe for **character consistency video** at scale. For alternative approaches, compare with Wan 2.6 Reference-to-Video.

The model still infers roles from image content — but with 3+ references, ambiguity increases and results become less predictable. With 1–2 references, implicit inference is usually fine. With 3+, always use `` tags to lock roles.

**16:9** (landscape) and **9:16** (portrait) at **720p**. Duration is 3–10 seconds per generation. Same format spec as the other Omni Flash video variants. For longer content, generate in segments and stitch — or for narrative sequences, consider Veo 3.

Roughly **~$0.13 per second** of output at 720p, pay-as-you-go, no subscription. A 5-second clip is around $0.65, an 8-second clip $1.00, a 10-second clip $1.30. Live pricing across every video model is on the JAI Portal model pricing dashboard.

Omni Flash Reference-to-Video is the pick when you need **audio + video from multi-references in one pass**. Seedance 2.0 Reference-to-Video is a strong alternative for silent higher-fidelity output. Wan 2.6 Reference-to-Video handles open-ended reference-guided workflows. Pick the tool that matches whether you need audio baked in.

⚖️ How Google Gemini Omni Flash Reference-to-Video Compares

**Google Gemini Omni Flash Reference-to-Video** is the JAI Portal pick when you need a **multi image video generator** with baked-in audio and **character consistency** across generations. For silent higher-fidelity output, compare with Seedance 2.0 Reference-to-Video. For open-ended reference-guided workflows, Wan 2.6 Reference-to-Video is the alternative. For simpler animate-a-still workflows, use the sibling Omni Flash Image-to-Video.

Google Gemini Omni Flash Reference-to-Video

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