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We are thrilled to announce that Gemini 3 Flash is now available within AlloyDB for PostgreSQL. Gemini 3 Flash is a high-speed, lightweight model within the Gemini 3 family, designed to balance efficiency with the advanced reasoning and multimodal capabilities of the 3.0 series. Released today as a successor to Gemini 2.5 Flash, it emphasizes low-latency and cost-effectiveness, making it the primary choice for high-throughput applications like real-time chatbots, rapid prototyping, and “vibe coding”.
While Gemini 3 Pro handles the most intensive logic-heavy tasks, Gemini 3 Flash provides the “thinking” capabilities necessary for complex agentic workflows, such as multi-step tool calling and long-context processing, while maintaining the speed and affordability required for mass-scale deployment.
Unlocking the Power of Gemini 3.0 Flash with AI Functions
You can unlock the power of Gemini 3 Flash in AlloyDB with just a few simple steps. By leveraging native AI functions such as AI.IF, AI.GENERATE and AI.RANK, you can access the new model — which has demonstrated a boost in accuracy compared to Gemini 2.5 Flash.
Use Case: Sentiment Analysis
Consider a scenario where an inventory agent must decide which products to feature on a homepage based on the last hour of customer feedback. Instead of building a complex sentiment classifier from scratch, we simply use the ai.if function. This acts as a cognitive filter: it processes the tone of the text to answer, ‘Does this review show a positive sentiment?’. This allows the agent to seamlessly filter the product_reviews table and retrieve a distinct list of top products that customers love, combining standard SQL precision (e.g., user filters for product category = ‘Electronics’ ) with the reasoning abilities of Gemini.
This integration allows AlloyDB to handle the heavy lifting of qualitative analysis. We can instantly isolate high-performing products in the ‘Electronics’ category, merging plain-text filtering of PostgreSQL with the intelligence of the 3.0-series model. Here’s a sample SQL query showcasing this.
SELECT product_name
FROM product_reviews
WHERE
ai.if(
prompt => 'Does this review show a positive sentiment ? Review: ' || product_review,
model_id => 'gemini-3-flash-preview')
AND product_category = 'Electronics';Give This a Spin Yourself!
Step1: First, register the model with AlloyDB if you haven’t already. Make sure to replace <project_name> with your project.
CALL
google_ml.create_model(
model_id => 'gemini-3-flash-preview',
model_request_url => 'https://aiplatform.googleapis.com/v1/projects/<project_name>/locations/global/publishers/google/models/gemini-3-flash-preview:generateContent',
model_qualified_name => 'gemini-3-flash-preview',
model_provider => 'google',
model_type => 'llm',
model_auth_type => 'alloydb_service_agent_iam');Step 2: Create the product_reviews table and add some data to it.
CREATE TABLE product_reviews (
product_name VARCHAR(100),
product_category VARCHAR(50),
product_review TEXT
);
INSERT INTO product_reviews (product_name, product_category, product_review) VALUES
('Wireless Headphones', 'Electronics', 'These headphones are amazing! Great sound quality and comfortable to wear.'),
('Smartwatch', 'Electronics', 'The battery life is terrible. Have to charge it every day.'),
('Espresso Machine', 'Home & Kitchen', 'Broke down after a few uses. Waste of money.'),
('4K Smart TV', 'Electronics', 'Amazing picture quality! Love watching movies on this TV.'),
('Portable Bluetooth Speaker', 'Electronics', 'Great sound for such a small speaker. Perfect for travel.');Step 3: Run a query combining the power of plain text search (product_category = ‘Electronics’) and the intelligence of Gemini 3.0 Flash (positive sentiment identification).
SELECT product_name
FROM product_reviews
WHERE
ai.if(
prompt => 'Does this review show a positive sentiment ? Review: ' || product_review,
model_id => 'gemini-3-flash-preview')
AND product_category = 'Electronics';+ - - - - - - - - - - - - - - +
| product_name |
| - - - - - - - - - - - - - - |
| Wireless Headphones |
| 4K Smart TV |
| Portable Bluetooth Speaker |
+ - - - - - - - - - - - - - - +
Voila! You just brought the world knowledge of Gemini Flash 3.0 to AlloyDB.
Want to learn more? Stay tuned for a deep-dive follow up blog on ‘SQL in the Gemini Era with AlloyDB’ — where we will walk through more practical examples of how to bring the power of Gemini 3.0 to AlloyDB through AI Functions.
Ready to get started? Spin up a free trial AlloyDB instance today and start building with Gemini 3.0 Flash. Explore how you can leverage AlloyDB AI’s features to supercharge your application.