gemini-2.5-flash

Model gemini-2.5-flash is used in 95 notebook(s) in this brain.

Concepts: Agent Engine · Agents & ADK · Applied Use Cases · Audio & Speech · Embeddings & Vector Search · Evaluation · Function Calling & Tools · Gemini Capabilities · Getting Started · Image & Video Generation · MLOps & Deployment · Open & Partner Models · Prompt Engineering · RAG & Grounding · Responsible AI · Tuning & Customization · Vertex AI Search · Vision

Notebooks

• Get started with Vertex AI Memory Bank — Builds a Vertex AI Memory Bank hotel concierge that stores and retrieves guest preferences across sessions.
• Customizing Memory Topics — Customizes Vertex AI Memory Bank topics for a financial advisor assistant and compares default vs custom extraction.
• Governance with Vertex AI Memory Bank — Builds a governed Vertex AI Memory Bank with TTL, topics, revision history, rollback, and cleanup.
• Get started with Memory Bank on ADK — Build ADK agents that generate, retrieve, preload, and customize Agent Engine Memory Bank memories.
• Building a Multimodal Trip Planner with ADK on Vertex AI Agent Engine Memory Bank — Builds and deploys a multimodal ADK trip planner using Vertex AI Agent Engine Memory Bank.
• Get started with A2A on Agent Engine — Builds, deploys, and queries an A2A Q&A agent on Vertex AI Agent Engine.
• Deploy your first agent to Vertex AI Agent Engine — Deploys ADK agents to Vertex AI Agent Engine with Express Mode, agent object, and inline source workflows.
• Get started with Agent Engine Terraform Deployment — Deploy Vertex AI Agent Engine agents with Terraform, cloudpickle packaging, and ADK tools.
• Get started with Cloud API Registry on Vertex AI Agent Engine — Builds and deploys an ADK BigQuery data analyst agent using Cloud API Registry on Vertex AI Agent Engine.
• Get started with Code Execution on Vertex AI Agent Engine — Runs LLM-generated Python securely with Vertex AI Agent Engine Sandbox and ADK agents.
• MCP on Vertex AI Agent Engine with custom installation scripts — Deploys a Reddit MCP tool agent to Vertex AI Agent Engine with custom install scripts.
• Building multi-agent systems with Vertex AI and Claude — Builds a Vertex AI Agent Engine multi-agent market analysis system with Gemini, Claude, ADK, A2A, and MCP.
• Building Multi-Agent Systems with Vertex AI and Llama model — Builds a traced Vertex AI multi-agent trading analyst with Gemini, Llama, ADK, A2A, and MCP tools.
• Get started with Sessions and Memory Bank for ADK agents in Cloud Run — Builds an ADK weather agent with Vertex AI Sessions, Memory Bank, and Cloud Run deployment.
• Get started with Sessions and Memory Bank for ADK agents in Google Kubernetes Engine — Builds an ADK weather agent with Vertex AI Sessions, Memory Bank, and GKE deployment.
• 🛡️ AI Brand Safety: Three-Tier Agent Anomaly Detection — Builds ADK agent anomaly detection with Gemini baselines, Vector Search scoring, and tiered audits.
• Vertex AI Agent Engine in Express Mode — Build, test, deploy, and query a Gemini ADK currency agent on Vertex AI Agent Engine Express Mode.
• Persisting LangChain History with Vertex AI Session Service — Persists LangChain chat and tool history in Vertex AI Agent Engine Session Service.
• Get started with Vertex AI Memory Bank - ADK — Builds an ADK agent with Vertex AI Memory Bank for long-term user memory across sessions.
• Get started with Vertex AI Memory Bank - CrewAI — Integrates Vertex AI Memory Bank with CrewAI agents for persistent long-term conversational memory.
• Get started with Vertex AI Memory Bank - LangGraph — Builds a LangGraph chatbot with Vertex AI Memory Bank for long-term personalized memory.
• Debugging and Optimizing Agents: A Guide to Tracing in Agent Engine — Builds, deploys, and traces a Gemini LangChain agent on Vertex AI Agent Engine.
• AG2 (formerly Autogen) Multi-Agents Example on Vertex AI Agent Engine — Builds and deploys an AG2 multi-agent research app to Vertex AI Agent Engine.
• Building and Deploying a Google Maps API Agent with Agent Engine — Builds, tests, deploys, and queries a Gemini Google Maps agent on Vertex AI Agent Engine.
• Building and Deploying a LangGraph Agent with Agent Engine in Vertex AI — Builds, tests, deploys, and deletes a Gemini LangGraph agent on Vertex AI Agent Engine.
• Building a Conversational Search Agent with Agent Engine and RAG on Vertex AI Search — Builds and deploys a Gemini movie-search RAG agent with LangChain, Agent Engine, and Vertex AI Search.
• Intro to Structured Output with the Gemini API — Shows how to make Gemini 2.5 Flash return JSON, enums, and schema-constrained multimodal outputs.
• Create & Deploy Agent and Run Gen AI Agent Evaluation — Creates, deploys, runs, and evaluates an ecommerce ADK agent on Vertex AI Agent Engine.
• Bring-Your-Own-Autorater using CustomMetric — Evaluates Gemini prompts with a client-side CustomMetric and a BYO Gemini autorater.
• Bring your own computation-based CustomMetric — Evaluates Gemini outputs with locally defined computation-based Vertex AI CustomMetric functions.
• Migrate from PaLM to Gemini model — Compares PaLM text-bison and gemini-2.5-flash with Vertex AI EvalTask for summarization migration.
• Compare Generative AI Models — Evaluates Gemini models on summarization with Vertex AI Gen AI Evaluation Service.
• Customize Model-based Metrics to Evaluate a Gen AI model — Shows how to customize Vertex AI Gen AI Evaluation model-based metrics for Gemini summarization outputs.
• Enhancing quality and explainability with Vertex AI Evaluation — Ranks Gemini answers with Vertex AI pairwise and pointwise evaluation explanations.
• Evaluate your autorater with meta-evaluation — Meta-evaluates Gemini autoraters on RewardBench with agreement and correlation metrics.
• Evaluate Generative Model Tool Use — Evaluates Gemini function calling and saved tool-call predictions with Vertex AI EvalTask metrics.
• Evaluate groundedness with custom parsing — Evaluates Gemini response groundedness with Vertex AI EvalTask and custom JSON parsing.
• Evaluate LangChain — Evaluates a LangChain recipe chatbot with Vertex AI Rapid Evaluation and custom Gemini-based metrics.
• Evaluating multimodal task — Evaluates image-grounded car damage labels with Vertex AI EvalTask and a Gemini custom autorater.
• Evaluating Agents - Evaluate a LangGraph agent with Vertex AI Gen AI Evaluation Service — Evaluates a LangGraph Gemini agent with Vertex AI Gen AI Evaluation metrics and BYOD data.
• Evaluating prompts at scale with Gemini Batch Prediction API — Evaluates Gemini image-classification prompts at scale with Batch Prediction and BigQuery.
• Intro to Batch Evaluations with the Gemini API — Runs asynchronous batch evaluation of Gemini responses with Vertex AI and Cloud Storage.
• Gen AI Evaluation Service SDK Preview-to-GA Migration Guide — Migrates Vertex AI Gen AI Evaluation SDK preview patterns to GA EvalTask, pointwise, and pairwise metrics.
• Rubric evaluation - Multimodal and Custom metric for text quality — Evaluates multimodal car-damage responses and text summaries with Vertex AI rubric-based metrics
• Evaluate and Optimize Prompt Template Design for Better Results — Compares Gemini prompt templates using Vertex AI EvalTask metrics to choose the best summarization prompt.
• Rubric-based instruction following evaluation using Gen AI Evaluation Service — Evaluates Gemini instruction following with rubric-based metrics in Vertex AI.
• Evaluate Gemini Structured Output — Evaluates Gemini structured JSON extraction from scanned order forms with Vertex AI Gen AI Evaluation.
• Use Gen AI Evaluation SDK to Evaluate Models in Vertex AI Studio, Model Garden, and Model Registry — Evaluates Gemini, Llama MaaS, Claude, and prompt templates with Vertex AI Gen AI Evaluation SDK.
• Evaluating Third-Party LLMs with the Vertex AI Gen AI Evaluation SDK — Evaluates third-party, MaaS, BYOM, and Gemini models with Vertex AI Gen AI Evaluation.
• Migrating Foundation Models: A Practical Guide with Gen AI Evaluation Serivce — Compares model migration candidates with Vertex AI Gen AI Evaluation and prompt optimization workflows.
• Gen AI Eval - Multi-turn Agent Eval, User Simulation, Metric Registration, Auto-Loss Analysis — Evaluates ADK travel agents with Vertex Gen AI Eval multi-turn simulation, custom metrics, and loss analysis.
• Getting Started: Quick Gen AI Evaluation — Evaluates gemini-2.5-flash responses with Vertex AI Gen AI Eval Service using a default quality rubric.
• Intro to Gemini 2.5 Flash — Introduces Gemini 2.5 Flash on Vertex AI with text, thinking, multimodal, tools, and structured output.
• Intro to Request and Response Logging with Gemini — Shows how to enable Gemini request-response logging to BigQuery, query logs, and disable logging.
• Intro to Agent Platform Multimodal Datasets — Builds Agent Platform multimodal datasets for Gemini tuning validation, resource estimates, tuning, and batch prediction.
• LlamaIndex RAG Workflows using Gemini and Firestore — Builds a LlamaIndex RAG workflow with Gemini, Vertex embeddings, and Firestore storage.
• Prompt Design - Best Practices — Demonstrates prompt design best practices for Gemini on Vertex AI with google-genai.
• Get Started with Vertex AI Prompt Optimizer — Shows zero-shot and data-driven prompt optimization with Vertex AI Prompt Optimizer.
• Get started with Vertex Prompt Optimizer - Custom metric — Optimizes a Gemini prompt with Vertex AI Prompt Optimizer using a custom Cloud Function metric.
• Get Started with Vertex AI Prompt Optimizer - Long prompt — Runs Vertex AI Prompt Optimizer to improve a long Gemini prompt using data-driven evaluation.
• Get Started with Vertex AI Prompt Optimizer - Multimodality — Optimizes a multimodal Gemini prompt with Vertex AI Prompt Optimizer on MathVista image QA.
• Get Started with Vertex AI Prompt Optimizer - Tool usage — Optimizes a Gemini tool-calling system instruction with Vertex AI Prompt Optimizer data-driven mode.
• Vertex Prompt Optimizer Notebook UI (Preview) — Shows how to configure, run, and inspect Vertex AI Prompt Optimizer jobs from a notebook UI.
• Evaluating Vertex RAG Engine Generation with Vertex AI Python SDK for Gen AI Evaluation Service — Evaluates Vertex AI RAG Engine responses with a custom Gen AI Evaluation Service metric.
• Vertex AI RAG Engine with Pinecone — Shows how to use Vertex AI RAG Engine with Pinecone as the vector database for Gemini retrieval.
• Vertex AI RAG Engine with Vertex AI Vector Search — Builds a Vertex AI RAG Engine corpus backed by Vertex AI Vector Search and queries it with Gemini.
• Intro to thought signatures — Shows how Gemini thought signatures preserve reasoning context across multi-turn function calling.
• Intro to thought signatures with REST API — Shows how to pass Gemini thought signatures through REST function-calling turns.
• Get Started with Gemini Preference Optimization — Tunes Gemini 2.5 Flash with human preference data using Vertex AI preference optimization.
• Supervised Fine-Tuning with integrated Gen AI Evaluation — Fine-tunes gemini-2.5-flash with automatic Gen AI Evaluation metrics at each checkpoint.
• Integrate Custom Metrics into Gemini Supervised Fine-Tuning — Adds a Python custom metric to Gemini SFT using Vertex AI REST tuning jobs and GCS outputs.
• Vertex AI SFT Gemini Migration Recipe — Migrates explicit SFT hyperparameters from gemini-1.5-flash-002 tuning jobs to gemini-2.5-flash.
• Supervised Fine Tuning with Gemini 2.5 Flash for Image Captioning — Fine-tunes Gemini 2.5 Flash on GCS image-caption pairs and evaluates ROUGE before and after tuning.
• Supervised Fine-tuning Gemini 2.5 Flash for Predictive Maintenance — Fine-tunes Gemini 2.5 Flash on simulated sensor data to classify equipment maintenance status.
• Supervised Fine Tuning with Gemini 2.5 Flash for Article Summarization — Fine-tunes Gemini 2.5 Flash on WikiLingua article summaries and evaluates ROUGE before and after tuning.
• Supervised Fine-tuning Gemini 2.5 Flash for Visual Defect Detection — Fine-tunes Gemini 2.5 Flash on image-based manufacturing defect classification.
• Intro to Url Context — Shows how to use Gemini URL context to summarize, compare, and analyze web pages with optional Google Search grounding.
• AI-Assisted Data Science Workflows in BigQuery — Builds a BigQuery multimodal housing workflow with Gemini enrichment, BQML clustering, and vector search.
• Semantic Analysis in BigQuery with AI Functions — Uses BigQuery AI functions with Gemini to rank, classify, filter, join, and enrich pet product data.
• BigQuery DataFrames ML: Prescription Drug Name Generation — Generates pharmaceutical brand name ideas with BigQuery DataFrames ML and Gemini.
• Introduction to Generative AI functions in BigQuery — Introduces BigQuery generative AI functions for SQL-based text analysis and forecasting.
• Analyze Multimodal Data in BigQuery — Shows BigQuery multimodal analysis over structured tables and GCS media using ObjectRefs and Gemini.
• Comparing LlamaIndex and LlamaParse for Dense Document Questioning Answering on Vertex AI — Compares LlamaIndex and LlamaParse RAG parsing methods for dense 10-Q document QA on Vertex AI.
• Evaluate — Evaluates Gemini-based document classification on image samples and visualizes confusion matrices.
• 🌿 Eco-Nomad Swarm: 100% Real-Data Sustainable Travel Orchestration — Builds a Vertex AI ADK travel swarm using Neo4j GraphRAG and live APIs for sustainable trip briefs.
• Gemini: An Overview of Multimodal Use Cases — Shows Gemini multimodal prompts for text, PDFs, images, video, audio, code, retail, diagrams, and comparisons.
• Know Your Customer Use Case - Gemini Grounding with Google Search — Builds grounded Gemini KYC negative-news reports and evaluates response quality with custom Vertex AI metrics.
• Video Captioning with Gemini — Uses Gemini on Vertex AI to generate rich multimodal captions from a video in Cloud Storage.
• Video Data Curation - Video Quality Filtering — Filters video datasets by metadata, OCR/watermarks, aesthetics, and motion scores for curation.
• Multimodal Sentiment Analysis with Gemini — Compares Gemini sentiment analysis on audio versus a transcript of the same conversation.
• Productivity Coaching with Gemini and Google Calendar — Uses Gemini 2.5 Flash with Google Calendar data to provide productivity coaching and schedule recommendations.
• Leverage LlamaIndex with Vertex AI Vector Search to perform question answering RAG — Builds LlamaIndex RAG on Vertex AI Vector Search, compares prompts, and adds multi-document agents.
• Detecting and Editing Visual Objects with Gemini — Detects visual objects with Gemini, crops them, and edits them with Gemini image models.
• Spatial understanding with Gemini 3 — Uses Gemini 2.5 Flash on Vertex AI to detect objects and draw normalized bounding boxes on images.
• Gemini Enterprise custom agent with Vertex AI session — Builds a Gemini Enterprise travel agent using ADK sub-agents and persistent Vertex AI sessions.

---

Model · All entities · Home