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Guide2026/07/06Updated 2026/09/01

Gemini Omni Flash API Tutorial: Model ID, Pricing, and Working Code

Gemini Omni Flash API is GA: model ID gemini-omni-1.1-flash, ~$0.10/sec, 720p with 1080p/4K upscaling, 3–10s clips extendable to 40s. Working Python, JS, and curl examples inside.

Gemini Omni Flash API Tutorial: Model ID, Pricing, and Working Code

Quick Answer

The Gemini Omni Flash API is live — and since August 27, 2026, generally available as Gemini Omni 1.1 Flash, model ID gemini-omni-1.1-flash. Google first opened the model to developers in public preview on June 30, 2026, under the legacy model ID gemini-omni-flash-preview; every example below uses the GA string. Pricing is $0.10 per second of 720p output video — a 10-second clip costs about $1.00, the same rate as Veo 3.1 Fast. 1.1 also adds a cheaper 360p draft tier, scene extension to 40 seconds, first/last-frame control, and 1080p/4K upscaling. The API generates 3–10-second base clips from text, images, or short video references, and its differentiating feature is conversational editing: you chain requests with previous_interaction_id via the Interactions API and refine a clip across turns instead of re-rolling it. If you were looking for a waitlist, you can skip it — a free API key from AI Studio is enough to run every example below. This tutorial covers setup, working Python, JavaScript, and curl examples for text-to-video, image-to-video, and multi-turn editing, plus the parameter table, the current limits, and the costs to model before production.

Key Takeaways

  • Generally available since August 27, 2026 via Google AI Studio, the Gemini API, and the Gemini Enterprise Agent Platform — preview ran June 30 to August 27.
  • Model ID: gemini-omni-1.1-flash (legacy: gemini-omni-flash-preview). It runs on the Interactions API (client.interactions.create), not the generate_videos pattern Veo uses.
  • Pricing: ~$0.10 per second of 720p output. 5 seconds = $0.50, 10 seconds = $1.00 — identical to Veo 3.1 Fast. 1.1 adds a 360p draft tier at about a third of the cost.
  • Output: 3–10-second clips at 720p, extendable to 40 seconds via 1.1's scene extension; 1080p and 4K available through upscaling.
  • Conversational editing is the headline feature. Pass previous_interaction_id to edit the prior result while the scene, characters, and physics carry over.
  • Hard limits today: video references capped at 3 seconds, no reasoning across multiple videos, no voice editing, and no temperature, system instructions, or negative prompts.

What shipped on June 30 — and what "public preview" means

Google announced developer access in its official launch post: Gemini Omni Flash opened "in public preview starting today in Google AI Studio and the Gemini API," alongside the generally available Nano Banana 2 Lite image model. Public preview meant the model string carried a -preview suffix, quotas were conservative, and Google reserved the right to change parameters before GA. That preview window closed on August 27, 2026, when Google announced Gemini Omni 1.1 Flash, generally available as gemini-omni-1.1-flash at the same per-second price. The examples below use the GA string. If you still have gemini-omni-flash-preview in a config value, swap it — the legacy string still works, but new work should target 1.1. Scene extension, first/last frame, 360p drafts, and 4K upscaling are covered in the 1.1 breakdown and the migration guide.

Consumer access hasn't changed: the Gemini app and Google Flow for AI Plus/Pro/Ultra subscribers, plus free generation inside YouTube Shorts and YouTube Create. What's new is that you can now call the same model programmatically.

Pricing: $0.10 per second of output

Clip lengthCost per generation
3 seconds$0.30
5 seconds$0.50
8 seconds$0.80
10 seconds$1.00

Three things to model before you wire this into a product:

  1. Edits bill like generations. Each conversational-edit turn renders new output seconds. A 5-second clip plus three refinement turns is ~$2.00, not $0.50.
  2. Draft at 360p when you are iterating. 1.1 added a cheaper 360p tier; 720p is still the default, and 1080p/4K come via upscaling. For look-and-feel experiments, cheap stills first is still the better pipeline — covered in our Nano Banana 2 Lite + Omni Flash workflow guide.
  3. Check your project's quota panel in AI Studio before load-testing. GA removed the preview-tier uncertainty, but published QPS still varies by project.

Setup

  1. Create a free API key in Google AI Studio.
  2. Install the SDK: pip install google-genai (Python) or npm install @google/genai (JavaScript).
  3. Export the key as GEMINI_API_KEY — both SDKs pick it up automatically.

Text-to-video

The Interactions API returns the video directly on the interaction object — note that this is a different shape from Veo's long-running generate_videos operations.

Python:

import base64
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-omni-1.1-flash",
    input="A marble rolling fast on a chain reaction style track, continuous smooth shot."
)
with open("marble.mp4", "wb") as f:
    f.write(base64.b64decode(interaction.output_video.data))

JavaScript:

import { GoogleGenAI } from '@google/genai';
import * as fs from 'fs';
const ai = new GoogleGenAI({});

const interaction = await ai.interactions.create({
  model: 'gemini-omni-1.1-flash',
  input: 'A marble rolling fast on a chain reaction style track, continuous smooth shot.',
});

if (interaction.output_video?.data) {
  fs.writeFileSync('marble.mp4', Buffer.from(interaction.output_video.data, 'base64'));
}

curl:

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?key=$GEMINI_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
     "model": "gemini-omni-1.1-flash",
     "input": "A marble rolling fast on a chain reaction style track, continuous smooth shot."
    }'

Prompting works the way it does in the consumer app: describe the shot, the motion, and the camera in plain language. Our prompt template library and the prompt gallery transfer directly.

Image-to-video and reference images

Mix image and text parts in the input array. A single image acts as the starting frame or a style/motion guide, depending on what your text asks for:

import base64
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-omni-1.1-flash",
    input=[
        {"type": "image", "data": base64_image, "mime_type": "image/jpeg"},
        {"type": "text", "text": "turn this into realistic footage, using the drawing only as a guide for movement, do not show the drawing in the final video"}
    ],
)
with open("clownfish.mp4", "wb") as f:
    f.write(base64.b64decode(interaction.output_video.data))

Multiple images work as subject references — the model composes them into one scene:

interaction = client.interactions.create(
    model="gemini-omni-1.1-flash",
    input=[
        {"type": "image", "data": cat_b64, "mime_type": "image/png"},
        {"type": "image", "data": yarn_b64, "mime_type": "image/png"},
        {"type": "text", "text": "A cat playfully batting at a ball of yarn."}
    ],
)

For the craft side of image-to-video — choosing source frames, writing motion prompts, keeping subjects consistent — see the image-to-video guide.

Conversational editing with previous_interaction_id

This is the feature no other video API currently matches. Instead of re-prompting from scratch, you reference the previous interaction and describe only the change; characters, scene, and physics carry over:

import base64
from google import genai

client = genai.Client()

# Turn 1: generate the initial video
res1 = client.interactions.create(
    model="gemini-omni-1.1-flash",
    input="A woman playing violin outdoors."
)

# Turn 2: edit the previous video
res2 = client.interactions.create(
    model="gemini-omni-1.1-flash",
    previous_interaction_id=res1.id,
    input="Make the violin invisible."
)
with open("example.mp4", "wb") as f:
    f.write(base64.b64decode(res2.output_video.data))

Google's launch post notes the Interactions API maintains session context for up to three sequential edits. The one-instruction-per-turn discipline we describe in the conversational editing guide applies verbatim here: small, single-change edits land far more reliably than compound ones.

Parameters and current limits

ParameterValuesNotes
aspect_ratio16:9, 9:16Landscape is the default
tasktext_to_video, image_to_video, reference_to_video, editOptional — the model infers it from your input if unset
previous_interaction_idinteraction ID stringRequired for multi-turn editing

Known limits on the GA 1.1 model, per Google's docs:

  • Base clips are 3–10 seconds at 720p, extendable to 40 seconds via scene extension. 1080p and 4K are available through upscaling; 360p is the cheap draft tier.
  • Video references are capped at 3 seconds, and reasoning across multiple input videos is not supported.
  • Voice editing is not supported.
  • No system instructions, temperature, top_p, stop sequences, or negative prompts — prompt text is the only steering wheel.
  • Regional availability is restricted in some markets; check the model page in Google's docs for your region.

For working around the 10-second cap specifically — storyboard stitching and last-frame chaining, with cost math — see how to make Omni Flash videos longer than 10 seconds.

FAQ

Is the Gemini Omni Flash API generally available?

Yes — since August 27, 2026. The GA model ID is gemini-omni-1.1-flash (no -preview suffix), priced at ~$0.10 per second of 720p output. The 1.0 preview string (gemini-omni-flash-preview, live since June 30, 2026) still works but is now the legacy path — new integrations should target 1.1. See the API status post for the full timeline.

How much does a 10-second video cost via the API?

About $1.00 — output is billed at $0.10 per second. Budget conversational edits at the same rate: each edit turn renders new output seconds.

Can I generate 1080p or 4K with Omni Flash?

Yes, on 1.1. Default output is still 720p; set resolution and use 1.1's upscaling path for 1080p or 4K. Draft at 360p when you are iterating. See Draft at 360p, upscale to 4K. Veo 3.1 remains an alternative if you want native 4K without the upscale step.

Do I need Vertex AI or an enterprise account?

No. A free API key from Google AI Studio is enough. Enterprise customers can also access the model through the Gemini Enterprise Agent Platform.

Can I use Omni Flash without writing code?

Yes — the Gemini app and Google Flow (AI Plus/Pro/Ultra), YouTube Shorts and YouTube Create for free, or the Omni Flash studio in the browser with no API setup.

Is Omni Flash affiliated with Google?

No. Omni Flash is an independent platform built for the Gemini Omni era. It is not affiliated with Google. Gemini, Gemini Omni, Omni Flash, Veo, and related names are trademarks of their respective owners.

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