AI TOOL SERIES — EPISODE 75: Everything Creators Need to Know about Google Omni AI
Google Omni was the focus of a recent internal AI product session at Techify, where the team demonstrated its multimodal capabilities, video generation workflow, image-to-video creation, and prompt-based video editing. The session showed how users can combine prompts, images, sketches, audio, and video to create and modify AI-generated content.
In this review, we break down what was demonstrated during the session, how Google Omni can be used to create professional videos, its editing capabilities, and the pricing comparison discussed during the demo.
What Is Google Omni AI?
Google Omni was presented during the session as a next-generation AI model capable of understanding multiple types of inputs, including text, images, audio, video, and sketches.
Unlike a workflow that relies exclusively on text prompts, the demonstrated approach allows users to combine different forms of input when creating or modifying content. For example, users can provide an existing image together with a prompt and ask the system to turn that image into a video with motion and animation.
The session also demonstrated the ability to work with an existing generated video and make targeted changes using an additional prompt.
This multimodal approach makes Google Omni particularly relevant for content creation, advertising, professional video generation, and visual editing workflows.
Key Google Omni AI Features
Here are the main capabilities demonstrated during the session.
Multimodal AI Input
One of the primary capabilities highlighted was Google’s ability to work with different types of media.
The session described support for:
- Text prompts
- Images
- Audio
- Video
- Sketches
- Combinations of multiple inputs
This means users aren’t restricted to describing an entire scene through text. Existing visual assets can also become part of the generation process.
Image-to-Video Generation
The demo showed how an existing image can be transformed into a video.
The workflow was relatively straightforward: the user selected an image, provided a prompt, and instructed the system to add motion and animation to the attached image.
For example, the demonstration used a prompt asking the system to use the attached image, introduce motion, and apply animation to make the result look more professional.
After processing, Google Omni generated a video from the supplied image and prompt.
Multiple Video Styles and Templates
The demonstration also showed several predefined video options available through the interface.
Some of the options mentioned during the session included:
- Montage
- Talking to Pat
- Anime
- 8-bit
- Adventure
- Career Day
These options provide different creative directions for video generation without requiring users to build every visual style from scratch.
Prompt-Based Video Editing
One of the more interesting capabilities demonstrated was the ability to modify an already-generated video using another prompt.
During the session, an example was given where a generated advertisement video needed its lighting changed.
Instead of generating a completely new video, the user could provide an additional instruction such as changing or dimming the lighting.
The system would then attempt to preserve the existing video while applying the requested modification.
This type of targeted editing can be useful when the original generation is already close to the desired result, and only a specific visual element needs to be changed.
Google Omni AI Demo: Creating a Video From an Image
The main demonstration focused on generating a video from an existing image.
The workflow followed during the session was:
Step 1: Open Google Gemini
The demonstration began inside Google Gemini, where the presenter selected the video creation functionality.
Step 2: Select Create Video
The presenter selected the video-generation option, which exposed several predefined creative choices.
Step 3: Select a Video Style
For the demonstration, the Montage option was selected.
Step 4: Add a Prompt
A prompt was entered instructing the system to use the attached image and introduce motion and animation.
Step 5: Upload an Image
An existing image was attached as a visual reference.
Step 6: Generate the Video
The system processed the prompt and image before producing the resulting video.
The demonstration showed how a relatively simple prompt combined with an existing visual asset could be used to produce a more dynamic video rather than starting from a blank text prompt.
Editing an Existing AI-Generated Video
The session also demonstrated a second workflow that goes beyond initial video generation.
Suppose an advertisement has already been generated but the lighting isn’t suitable for the intended presentation.
Instead of starting over, the user can provide another instruction asking the system to modify the lighting.
The example discussed during the session was essentially:
Change or dim the lighting.
The intended result is to preserve the other elements of the generated video while modifying the requested visual property.
This can make iterative content creation more efficient because creators can refine an existing generation instead of repeatedly rebuilding the entire scene.
Google Omni vs. Higgsfield AI
The session also included a brief comparison between Google Omni and Higgsfield AI.
According to the discussion, Higgsfield was described as being more focused on cinematic video creation and providing templates designed around that workflow.
Google Omni, on the other hand, was presented during the session as being useful for generating professional videos and advertisement-oriented content.
The practical distinction discussed was therefore more about the intended workflow than simply video quality.
| Feature | Google Omni | Higgsfield AI |
| Image-to-video | Demonstrated | Available |
| Text-based generation | Demonstrated | Available |
| Multiple media inputs | Highlighted | Depends on workflow/model |
| Video editing through prompts | Demonstrated | Targeted revisions available |
| Advertisement creation | Highlighted in session | Marketing-oriented features |
| Cinematic video creation | Supported through demonstrated workflow | Strong focus in session |
| Templates/styles | Multiple options demonstrated | Template-based workflows |
| Existing image as reference | Demonstrated | Supported |
The comparison above reflects the capabilities and positioning discussed during the product session rather than an independent benchmark of the two platforms.
Google Omni AI Pricing
Pricing was briefly discussed during the session.
The presenter mentioned that the Google offering being used showed a cost of approximately $400 plus taxes, while Higgsfield was mentioned at approximately $59 per month at the time of the session.
The session also stated that the Google offering could be used for generating multiple images and videos during the month.
Because the transcript does not provide the exact Google plan name, credit allocation, usage limits, billing period, or current pricing structure, these figures should be treated as the pricing discussed during the session rather than a complete current pricing breakdown.
| Platform | Price Mentioned During Session | Primary Use Discussed |
| Google Omni | $400+ plus taxes | Images, videos and professional/advertising content |
| Higgsfield | $59/month | Cinematic video creation and templates |
Pros and Cons of Google Omni AI
Pros
- Multimodal input: The session highlighted support for text, images, audio, video, and sketches.
- Image-to-video generation: Existing images can be used as the starting point for video generation.
- Prompt-based modifications: Existing generated videos can be modified with additional instructions.
- Multiple creative styles: Several predefined video-generation options were demonstrated.
- Advertising applications: The session specifically demonstrated professional and advertisement-oriented use cases.
- Iterative workflow: Users can refine generated content rather than necessarily starting from scratch.
Cons
- Pricing: The cost discussed during the session was significantly higher than the Higgsfield subscription mentioned in the comparison.
- Generation time: The demonstrated video generation required some processing time.
- Limited pricing details: The session did not cover detailed credit limits, generation quotas, or the exact usage restrictions of the Google offering.
- Output control: While targeted modifications were demonstrated, the session did not provide a detailed comparison of how precisely every type of visual change can be controlled.
Google Omni AI Use Cases
Based on the demonstrations in the session, Google Omni can be useful for several types of creative workflows.
Advertisement Creation: The ability to generate videos from images and subsequently modify aspects such as lighting can be useful for advertising workflows.
Social Media Content: The availability of different video styles and relatively simple prompt-based generation can help create visual content for digital platforms.
Product Videos: Existing product images can potentially be turned into animated video content by combining them with appropriate prompts.
Professional Video Content: The session specifically demonstrated the use of the platform for creating professional-looking video content from existing visual assets.
Creative Prototyping: Creators can quickly experiment with different visual directions using prompts, images, and predefined styles before deciding on a final production direction.
Frequently Asked Questions About Google Omni AI
1. What is Google Omni AI?
Google Omni was presented in the session as a next-generation multimodal AI model capable of working with text, images, audio, video, sketches, and combinations of these inputs.
2. Can Google Omni create videos from images?
Yes. The demonstration showed an image being uploaded alongside a prompt, after which the system generated a video incorporating motion and animation.
3. Can I edit an AI-generated video using Google Omni?
The session demonstrated prompt-based modifications to an already-generated video. For example, the presenter showed how a prompt could be used to change or dim the lighting without intentionally changing the other elements of the video.
4. Can Google Omni generate advertisement videos?
Advertisement and professional video creation were specifically discussed during the session. The demonstration included generating a video from an image and then modifying its lighting for an advertising-style workflow.
5. What types of input does Google Omni support?
The session highlighted text, images, audio, video, sketches, and combinations of these inputs.
6. How much does Google Omni cost?
The session mentioned a price of approximately $400 plus taxes for the Google offering being demonstrated. The transcript does not provide enough information to identify the exact plan or its complete usage limits, so current pricing should be checked separately before purchasing.
7. How is Google Omni different from Higgsfield?
The session positioned Higgsfield more toward cinematic video creation and templates, while Google Omni was discussed in the context of multimodal generation, professional video creation, and advertisement workflows.
Final Verdict: What Does Google Omni Bring to AI Video Creation?
The Google Omni session demonstrated a shift from simple text-to-video generation toward a more multimodal creative workflow.
Instead of relying solely on a written prompt, users can combine images, text, sketches, audio, and video as inputs. The demonstration also showed that the workflow can continue after the initial generation, with additional prompts being used to modify elements such as lighting.
For teams working on advertisements, professional visual content, and AI-assisted video production, these capabilities can make the creation and refinement process more flexible.
The main consideration discussed during the session is pricing. The Google offering demonstrated was quoted at approximately $400 plus taxes, compared with the approximately $59 monthly Higgsfield cost mentioned during the comparison. The exact value of each option will depend on the user’s required volume, generation type, and workflow.
Overall, the session showed how multimodal AI is moving beyond generating content from scratch and toward creating, refining, and editing visual content through a combination of media and natural-language instructions.
