Gemini Omni Flash (Google DeepMind)

Gemini Omni is Google DeepMind's video generation and editing model family, announced at I/O 2026. The first model, Gemini Omni Flash (gemini-omni-flash-preview, developer access since June 30, 2026), generates 3-10 second clips at 720p/24fps with synthesized audio via the Gemini Interactions API. Its differentiator in the OpenMontage fleet is stateful conversational editing: each generation returns an interaction_id, and a follow-up call with previous_interaction_id edits that video in place — no other wrapped provider can refine a clip without regenerating it.

OpenMontage wraps it as gemini_omni_video (native Gemini API, no gateway). It shares GOOGLE_API_KEY/GEMINI_API_KEY with google_imagen and google_tts — one key, three capabilities. Paid tier only: ~$0.10 per second of output video (billed as 5,792 output tokens/sec at $17.50/1M).

When to pick it (and when not)

Use it for	Prefer another provider for
Iterative refinement — generate, review, then edit the same clip in layers	One-shot cinematic hero clips (→ Seedance 2.0, see seedance-2-0)
Editing an existing/uploaded clip (restyle, add/remove objects, change text)	Clips longer than 10s or above 720p
On-screen rendered text and word-by-word text beats	Seed-reproducible generations (no seed support)
Reference-image-bound subjects/styles via prompt tags	First/last-frame interpolation (→ veo_video)
Timecode-scheduled multi-beat clips from one prompt	Non-English narration (English only fully supported)

Route through video_selector for generation operations. Editing (edit_video) is a direct-tool operation — call gemini_omni_video from the registry, because the multi-turn interaction state lives outside the selector's model.

Generation prompting

Describe scene + camera + lighting + motion + audio. Official example:

Continuous, unbroken handheld shot of a fluffy tabby cat sitting on a sunny windowsill, looking out into a leafy garden. The cat's tail twitches slowly, and its ears rotate slightly toward ambient noises. Sunbeams illuminate dust motes in the air.

• Force a single shot explicitly: "In a single continuous shot," / "No scene cuts." Otherwise the model may cut between scenes.
• Negatives go in prose — there is no negative_prompt parameter: "No dialogue," "No extra sound effects."
• No sampler controls: system instructions, temperature, top_p, and seeds are all unsupported. The prompt is the only lever.
• Meta-prompt for quality: "Consider micro-detail, expression and timing to create a very rich, detailed but entirely natural scene."

Timecode syntax

Schedule beats with bracketed ranges or natural language — this maps directly onto OpenMontage scene-plan timings:

[0-3s] A person is walking [3-6s] They stop and turn around

"After 3 seconds, a woman enters the scene." / "At 5s the chorus starts in the background audio."

Audio and on-screen text

Audio is synthesized automatically; direct it in the prompt: "Include calm background music," "The audio is a low tinny radio broadcast in the background." Rendered text works and can be timed:

One word on the screen at a time: 'did, you, know, that, Omni, can, do, awesome, text?' Each word appears for 1s.

Reference images (<FIRST_FRAME> / <IMAGE_REF_N> tags)

Pass local images via reference_image_paths (they are sent in order), then bind them to roles inside the prompt with tags. <IMAGE_REF_N> indexes from 0 in the order supplied:

in the style of <IMAGE_REF_0> a woman <IMAGE_REF_1> is walking

[0-3s] A studio fashion sequence. Starting with woman <IMAGE_REF_0>, she is
holding <IMAGE_REF_1> [3-6s] Then we see the man <IMAGE_REF_2> holding <IMAGE_REF_3>

• <FIRST_FRAME> makes an image the opening frame: <FIRST_FRAME> a woman is walking.
• Use high-resolution images; describe the intended motion specifically rather than "make it move."
• Say what each image is (product / character / style / background reference) — the model decides usage from context.

Conversational editing (the differentiator)

Editing prompts are the opposite of generation prompts: short and surgical. Overly descriptive edit prompts cause unintended changes.

1. Generate the base clip (subject + scene + motion). The tool returns interaction_id in its result data.
2. Pass it back as previous_interaction_id with operation="edit_video" and describe only the delta.
3. Append "Keep everything else the same." to pin unmentioned elements.
4. Refine in layers — one turn for lighting, one for camera, one for action, one for audio.

Official good/bad pairs:

Avoid	Instead
"In the video of the man sitting on the sofa, please add a small black cat..."	"Add a cat that jumps onto his lap, he begins to pet it. Keep everything else the same."
"Please remove the cell phone... and fill in the background so it looks like..."	"Make the phone invisible. Keep everything else the same."

Other working edit prompts: "Make this video anime" / "Put a fashionable hat on this person" / "Change the lighting to be more dramatic" / "Change the text on the sign to say 'Omni Flash'".

Gotcha — store: editing via previous_interaction_id only works if the prior call kept the interaction server-side (store defaults to true in gemini_omni_video). Set store=false only for one-shot generations you will never edit.

Editing uploaded videos: pass input_video_path instead of previous_interaction_id; the tool uploads it via the Files API. Unavailable in the EEA, Switzerland, and the UK (editing generated videos works everywhere).

Hard limitations (preview)

• Output: 3-10s, 720p, 24fps, MP4 with audio; aspect ratio 16:9 or 9:16. All output carries an invisible SynthID watermark.
• No seed, negative prompt, temperature, top_p, or system instructions.
• No video extension or first/last-frame interpolation; no voice editing.
• Audio reference inputs unsupported. Video references ≤3s are accepted by the schema but not processed correctly — don't rely on them.
• Multi-video prompting unsupported; may degrade output.
• English fully supported; other languages untested.
• Images of minors (EEA/CH/UK) and certain recognizable people are blocked for upload/editing.

Sources

• Generation & editing guide: https://ai.google.dev/gemini-api/docs/omni
• Model card: https://ai.google.dev/gemini-api/docs/models/gemini-omni-flash
• Pricing: https://ai.google.dev/gemini-api/docs/pricing
• Announcement: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-omni/