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Google’s latest Open Source model, Gemma 3, is not the only big news in the alphabet subsidiary today.
No, in fact, the spotlights may have been stolen by Google gemini 2.0 flash with native image generationA new experimental model available for free for Google AI Studio users and developers via the Google Gemini API.
It marks the first time that a large American technological company has sent the generation of multimodal images directly within a model to consumers. Most of the other AI image generation tools were diffusion models (image specific) connected to large language models (LLM), requiring a little interpretation between two models to derive an image that the user required in a text prompt.
On the other hand, Gemini 2.0 Flash can generate images natively in the same model as the text of the guest types invites, theoretically allowing greater precision and more capacities – and the first indications are quite true.
Gemini 2.0 Flash, unveiled for the first time in December 2024, but without the capacity for generation of native images activated for users, integrates multimodal entry, reasoning and understanding of natural language to generate images alongside the text.
The newly available experimental version, Gemini-2.0-Flash-Exp, allows developers to create illustrations, refine the images by conversation and generate detailed visuals according to global knowledge.
How Gemini 2.0 Flash improves the images generated by AI
In a Blog article oriented developers Published earlier in the day, Google highlights several key capacities of Gemini 2.0 Flash’s Native image generation:
• Text and image narration: Developers can use Gemini 2.0 Flash to generate illustrated stories while maintaining consistency in characters and parameters. The model also responds to the comments, allowing users to adjust history or modify the artistic style.
• Conversational image edition: AI supports Multi-tours editionThis means that users can refine an image by providing instructions through natural language prompts. This feature allows real -time collaboration and creative exploration.
• Global generation of knowledge -based images: Unlike many other image generation models, Gemini 2.0 Flash uses wider reasoning capacities to produce more relevant contextually. For example, it can illustrate recipes with detailed visuals that align with real world ingredients and cooking methods.
• Improved text rendering: Many models of IA images have difficulty generating readable text in images, often producing spelling mistakes or distorted characters. Google reports that Gemini 2.0 Flash surpasses the main competitors In the rendering of the text, making it particularly useful for advertisements, publications on social networks and invitations.
The first examples show incredible potential and promise
Googlers and certain Power AI users to share examples of the new generation of images and publishing capacities offered via Gemini 2.0 Flash Experimental, and they were undoubtedly impressive.
Researcher Google Deepmind Robert Riachi presented How the model can generate images in a pixel-art style, then create new ones in the same style according to the text prompts.
Ai News Store Testingcatalog News Reported to the deployment of the multimodal capacities of Gemini 2.0 Flash Experimental, noting that Google is the first major laboratory to deploy this functionality.
User @Angaisb_ aka “angel” Has showed in a convincing example how an prompt to “add chocolate net” changed an existing image of croissants in a few seconds – revealing the rapid and precise image modification capacities of Gemini 2.0 via simply the back and forth with the model.
Theoretically media youtuber Underlined that this progressive modification of image without complete regeneration is something that the AI industry has long, demonstrating how it was easy to ask Gemini 2.0 Flash to modify an image to raise the arm of a character while preserving the rest of the image.
The old Googler transformed Ai Youtuber Bilawal Sidhu have shown how the black and white images colored, alluding to potential applications for historical catering or creative improvement.
These first reactions suggest that AI developers and lovers consider that Gemini 2.0 Flash as a very flexible tool for iterative design, creative narration and AI -assisted visual edition.
SWIFT deployment also contrasts with the OPENAI GPT -4O, which previewed the generation of native images capacities in May 2024 – almost a year ago – but has not yet published the publicly functionality – allowing Google to enter the opportunity to lead in the multimodal deployment of AI.
As a user @ Chatgpt21 aka “chris” underlined X, Openai in this case “los[t] The year + advances ”on this ability for unknown reasons. The user invited anyone from Openai to comment on why.
My own tests revealed certain limits with the size of the appearance report – it seemed stuck in 1: 1 for me, despite the text of modifying it – but it was able to change the direction of the characters in an image in a few seconds.
Although a large part of the first discussions on the generation of native images of Gemini 2.0 Flash has focused on individual users and creative applications, its implications for business teams, developers and software architects are important.
Design and marketing powered by AI on a large scale: For marketing teams and content creators, Gemini 2.0 Flash could serve as a profitable alternative to traditional graphic design work flows, automating the creation of brand content, advertisements and social media visuals. Since it supports text rendering in images, it could rationalize the creation of ads, the design of packaging and promotional graphics, reducing dependence on manual edition.
Improved developer tools and AI workflow: for CTOs, CIOs and software engineers, native images generation could simplify the integration of AI into applications and services. By combining text and image outputs in a single model, Gemini 2.0 Flash allows developers to build:
- Design assistants fed by AI generate UI / UX models or App.
- Automated documentation tools that illustrate real -time concepts.
- Dynamic narration platforms focused on AI for media and education.
Since the model also supports the conversational image editing, the teams could develop AI -centered interfaces where users refine the conceptions by natural dialogue, lowering the barrier to the entrance for non -technical users.
New possibilities of productivity software focused on AI: For business teams that build productivity tools powered by AI, Gemini 2.0 Flash could support applications such as:
- Automated presentation generation with slides and visuals created by AI.
- Anotation of legal and commercial document with infographics generated by AI.
- Visualization of electronic commerce, dynamically generating products of products based on descriptions.
How to deploy and experience this ability
Developers can start testing gemini 2.0 flash generation of images using the Gemini API. Google provides an example of an API request to demonstrate how developers can generate illustrated stories with text and images in a single answer:
from google import genai
from google.genai import types
client = genai.Client(api_key="GEMINI_API_KEY")
response = client.models.generate_content(
model="gemini-2.0-flash-exp",
contents=(
"Generate a story about a cute baby turtle in a 3D digital art style. "
"For each scene, generate an image."
),
config=types.GenerateContentConfig(
response_modalities=["Text", "Image"]
),
)By simplifying the generation of images powered by AI, Gemini 2.0 Flash offers developers new ways of creating illustrated content, designing AI assisted applications and experimenting visual narration.
