Google is on a spree updating their GenAI stack with their all-new Gemini 2.0 Flash Experimental. The major updates have been made with their deep research and image generation features. With its text and image processing capabilities, the model has the potential to significantly improve our interactions with chatbots. It is set to bring a visual element to our conversations. In this blog, we will explore image generation with the Gemini 2.0 Flash (Experimental) model, understand its features, and test its capabilities. Let’s start.
Gemini 2.0 Flash (Experimental) is a multimodal model by Google that seamlessly integrates text and image generation under a single simplified framework. The 2.0 Flash (Experimental) LLM was launched in December for a small pool of testers, it is now available for developer experimentation via Google AI Studio and the Gemini API.
Gemini 2.0 Flash comes with a great set of capabilities. It caters to a diverse set of issues that we usually see with most of the image generation models like their inability to:
Along with important added functionalities, the Gemini 2.0 Flash model comes with the following features:
You can access the Gemini 2.0 Flash(experimental) either via Google AI Studio or through Gemini API.
Via Google AI Studio:
Once signed in, from the “Run Settings” panel on the right hand side, under the “Model” dropdown, select “Gemini 2.0 Flash Experimental”.
Via Gemini API:
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"]
),
)
Also Read: I Tried All the Latest Gemini 2.0 Model APIs for Free
I will now test Gemini 2.0 Flash Experimental on 4 different tasks:
Now I’ll try each of these tasks with simple prompts. Let’s start with the first one:
Prompt: “Generate a 5-part story of a group of kids unboxing a treasure, inside which is a new red coloured chocolate bar, in 3D cartoon style. Generate an image for each scene.”
Output:
The output is a great amalgamation of text and images. The story is well written and the visuals are quite detailed. It feels like you are reading a comic book. With this feature, content creators and marketers can creatively bring their ideas to life.
Prompt: “add a bed in the middle of the room, opposite to the window, and add a painting on the center wall”
Output:
The image editing with Gemini 2.0 Flash (experimental) is quite easy. The model follows the prompts exactly and gives the result. Although in some instances, it might not exactly follow the instructions, this usually happens when there are more tasks in a single prompt. Yet overall, the model can be a great tool for visualising ideas.
Prompt: “Give me the recipe to bake a strawberry cheesecake. Please give an image for each step.”
Output:
The output is a detailed guide to baking a cheesecake, complete with accurate text and corresponding images for each step. The model successfully generated both the instructions and visuals, bringing clarity throughout the process. This capability makes it particularly valuable for creating comprehensive manuals for machines and emerging technologies, where step-by-step guidance with visuals is essential.
Prompt: “create a billiboard, with a light background and words written in orange text “We are Back, ORDER NOW” with a small Pizza placed next to the text”
Output:
The response is truly impressive! The output not only delivered the text exactly as I specified, in the desired color, but also included a small image of a pizza as requested. Few models have successfully integrated text within images, but Gemini 2.0 Flash (Experimental) excels in seamlessly combining both elements. This level of precision and adherence to prompt details sets it apart from many existing models!
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Image generation with Gemini 2.0 Flash (Experimental) is impressively efficient, offering a seamless and conversational approach to creating and refining images. It feels as if you’re chatting your way through the creative process, making adjustments in real-time. However, the model does have a few limitations.
Despite these drawbacks, Gemini 2.0 Flash demonstrates immense potential, paving the way for advanced AI-driven image generation in the future.
Also Read: Is o3-mini Better Than o1 for Image Analysis?
Gemini 2.0 Flash Experimental has diverse applications across industries, enabling seamless integration of text and image generation.
These capabilities make Gemini 2.0 Flash Experimental a powerful tool for design, marketing, education, and business applications, streamlining creative workflows with AI-driven efficiency.
Also Read: Google’s Gemma 3: Features, Benchmarks, Performance and Implementation
Gemini 2.0 Flash (Experimental) brings a significant turn in AI-driven image generation, bringing a new level of interactivity and multimodal capabilities to large language models. Its ability to easily integrate text and visuals makes it a powerful tool for a wide range of applications – from storytelling and marketing to real-world simulations and instructional content. While the model has some limitations, such as the lack of aspect ratio control and occasional inconsistencies in following prompts, its strengths in conversational editing, world knowledge, and accurate text rendering set it apart.
As AI continues to evolve, Gemini 2.0 Flash paves the way for a future where chatbots are not just text-based assistants but also creative visual collaborators.
I could show only a few examples of image generation using the new Gemini 2.0 Flash, but it can do much more. GenAI is so vast and impact our work in so many ways. In order to learn how to use it for improving you workflows – checkout our Free Course on Generative AI a Way to Life!
A. Gemini 2.0 Flash (Experimental) is Google’s latest multimodal AI model that integrates both text and image generation. It allows users to generate and edit images conversationally, making AI-driven visuals more interactive and responsive.
A. You can access Gemini 2.0 Flash (Experimental) via Google AI Studio by visiting the platform, signing in, and selecting “Gemini 2.0 Flash Experimental” under the Run Settings panel. Alternatively, you can use the Gemini API by specifying the “gemini-2.0-flash-exp” model in your API calls to generate text and images.
A. Some of the key features are:
– Multimodal Capabilities: Generates both text and images in a single model.
– Conversational Image Editing: Modify images dynamically through dialogue.
– Enhanced World Understanding: Creates images with real-world accuracy.
– Superior Text Rendering: Produces legible and well-formatted text in images.
A. No, the model currently does not support custom aspect ratios. It generates images in a predefined format, though future updates may include aspect ratio adjustments.
A. While it generally adheres well to prompts, there may be occasional discrepancies in fine details, especially for complex or highly specific requests.