TECHNICAL GUIDE Published

Gemini API and Vertex AI (now Agent Platform): A Comprehensive Guide to Integrating Generative AI into Your Business

Everything you need to know to choose the right platform, understand pricing, and take Gemini models to production—with verified data from official Google Cloud sources.

Emmanuel Armendariz
Emmanuel Armendariz
The Cloud Collective · · 12-minute read

Google offers access to its Gemini models through two main gateways: the Gemini Developer API (also known as Google AI Studio) and the Gemini API on Gemini Enterprise Agent Platform (formerly Vertex AI ). Both provide access to the same models, but they are designed for very different audiences and needs.

If your company is evaluating how to integrate generative AI into its products, processes, or applications, this guide will help you understand the key differences, up-to-date pricing, and real-world use cases driving companies of all sizes.

Gemini Developer API — The fastest path for developers. Direct API key, generous free tier, ideal for prototypes and small-to-medium applications.

Agent Platform Gemini API — The enterprise platform. Advanced security with IAM, data residency, guaranteed SLA, integration with BigQuery and Cloud Storage, and over 200 models in Model Garden.

The big news is that both APIs now share the Google Gen AI SDK unified, allowing migration from one to the other with minimal code changes:

// Gemini Developer API
const ai = new GoogleGenAI({ apiKey: your api key });

// Agent Platform (formerly Vertex AI ) — same library, a different line
const ai = new GoogleGenAI({ vertexai: true, project: "your-project", location: "europe-west1" });

Direct comparison

Same models, different entry point. Here are the differences that matter:

Characteristic Gemini Developer API Agent Platform Gemini API
HearingDevelopers, startups, prototypesEnterprises, ML teams, production at scale
AuthenticationSimple API keyIAM + Service Accounts
Free tierYes — free tokens on selected models$300 in credits for new users + free previews
Guaranteed SLANoYes — Agent Platform SLA
Data residencyNot configurableRegional endpoints (EU, US, Asia…)
Cloud integrationLimitedBigQuery , Cloud Storage, Agent Studio, Model Garden
ModelsGemini , Nano Banana, Veo, and Omni200+ ( Gemini , Claude , Llama, Gemma, DeepSeek…)
BillingPrepaid (Google AI Studio is transitioning postpaid accounts to prepaid)Google Cloud Billing with volume discounts
SDKUnified Google Gen AI SDK (Python, Node.js , Go, REST)

Gemini models and pricing — September 2026

✓ Verified gemini api September 29, 2026

The current family is the 3.x generation. The 2.5 models remain active, but Google limits access to existing users and recommends 3.8 Flash or 3.5 Flash-Lite for new projects. All of them support a 1-million-token context window.

MORE ADVANCED
Gemini 3.1 Pro Preview

The most capable model for complex reasoning, multimodal capabilities, and agents.

Input ≤200K$2.00/1M tokens
Output ≤200K$12.00/1M tokens
Input >200K$4.00/1M tokens
Output >200K$18.00/1M tokens
Gemini 3.8 Flash

Google's smartest Flash: autonomous agents, software development, and complex enterprise workflows.

Input$0.75/1M tokens
Output (incl. thinking)$3.75/1M tokens
From January 1, 2027$1.50 / $7.50
Free tier available
Gemini 3.5 Flash-Lite

Efficient model for high-volume agentic tasks, translation, and data processing.

Input (text/image/video/audio)$0.30/1M tokens
Output (incl. thinking)$2.50/1M tokens
Free tier available
Gemini 3.1 Flash-Lite

The most economical model of the current generation. Scheduled for discontinuation starting May 7, 2027 (replacement: 3.5 Flash-Lite).

Input (text/image/video)$0.25/1M tokens
Input (audio)$0.50/1M tokens
Output (incl. thinking)$1.50/1M tokens
Free tier available

⚠ Discontinued models and changes: Gemini 3 Pro Preview was retired on March 9, 2026 (replacement: 3.1 Pro Preview). Gemini 2.0 Flash and 2.0 Flash-Lite were retired on June 1, 2026. Imagen 4 became unavailable in the Gemini API on August 17, 2026 (replacement: Gemini 3.1 Flash Image), and Veo 2.0/3.0 on June 30, 2026 (replacement: Veo 3.1). The recommended replacement for Gemini 3 Flash Preview is 3.6 Flash. If you use any of these models, please plan your migration.

Gemini 3 models support the Batch API and inference Flex, which reduce costs by 50%. For workflows that do not require an immediate response, this is the most direct way to reduce the bill.

The paid tier includes 5,000 free Google Search grounding searches per month (shared across Gemini 3.x models). Thereafter, $14 per 1,000. Grounding with Google Maps follows the same structure.

In addition to text/reasoning models, Google offers: Gemini 3.8 Live for real-time voice, Gemini 3 Pro Image y 3.1 Flash Image (Nano Banana) for image generation, Gemini Omni Flash y Veo 3.1 for video, and Gemini 3.8 Flash TTS for voice.

Agent Platform (formerly Vertex AI ): much more than a model API

While the Gemini Developer API is a direct gateway to the models, Agent Platform is a comprehensive ecosystem for building, deploying, and governing AI applications at enterprise scale.

1

Model Garden: Over 200 models on one platform

Gemini , Anthropic 's Claude , Llama, Gemma, DeepSeek, GLM, and specialized models. Choose the right model for each task without switching platforms.

2

Agent Studio and Agent Runtime

Design, deploy, and scale autonomous agents using Agent Studio (low-code), ADK (code), and Agent Runtime (formerly Agent Engine, a managed runtime). Sessions and Memory Bank are in General Availability (GA), with billing starting September 1, 2026. Compatible with MCP and over 100 enterprise connectors.

3

Grounding with Google Search and Maps

Connect model responses to real-time data from the web, Google Maps, or your own enterprise data using Agent Search (formerly Vertex AI Search). Eliminate hallucinations and ground every response.

4

Full multimodal generation

Gemini 3.1 Flash Image for images, Veo 3.1 for video (including Lite for scale), Chirp for speech-to-text, and native Gemini models with integrated text-to-image generation.

5

enterprise security and governance

Granular IAM, VPC Service Controls, regional data residency (including Europe), and auditing with Cloud Logging/Monitoring. Your data is never used to train public models.

6

Prompt and evaluation environment (formerly Vertex AI Studio)

A visual interface for testing prompts, evaluating models (including partners like Claude ), comparing responses, and sharing configurations. Your AI laboratory in the browser.

Companies already using it in production

Real-world examples of companies integrating Gemini via Agent Platform (formerly Vertex AI ) to transform operations:

Shopify

It created Sidekick, a multimodal assistant powered by Gemini Live API on Agent Platform (formerly Vertex AI ) that offers real-time support. Users forget they are talking to AI.

UWM

Integrated native Gemini audio for voice agents, generating over 14,000 loans and increasing the resolution rate from 40% to 60%.

SightCall

Combine computer vision and Gemini 's native audio for real-time visual support assistants with Xpert Knowledge.

Databricks & JetBrains

Improvements of up to 15% in enterprise benchmarks are reported when using Gemini 3.1 Pro for reasoning over structured and unstructured data.

Napster

Use Gemini Live API to create AI companions that see the user's screen and respond like natural conversation experts—without the need for manual prompting.

Which one to choose? Your roadmap

The recommended path is progressive: start for free, build with the API , and scale with Agent Platform.

Step 1 — Experiment

Google AI Studio (Free). Test prompts with Gemini 3.8 Flash and 3.5 Flash-Lite, validate your concept, and refine your approach. Cost: $0.

↓
Step 2 — Build

Gemini Developer API (paid tier). Integrate the models into your application using API key. Enable prepaid billing once you exceed the free tier.

↓
Step 3 — Scale

Agent Platform. When you need enterprise security, compliance, SLAs, EU data residency, or greater reliability. Migration is straightforward thanks to the unified SDK .

For companies in the EU: If regulatory compliance ( GDPR ) and data residency are requirements, Agent Platform is the straightforward choice. Its regional endpoints in Europe ensure that your data is processed where you need it to be. The Gemini Developer API does not offer these guarantees.

Cost optimization: practical keys

Token-based pricing can scale rapidly in production. Here are the most effective strategies:

Context caching

Reuse frequent contexts (long system prompts, reference documents) to reduce billed input tokens. The cost of caching is minimal compared to reprocessing each time.

Batch API — 50% savings

Process requests asynchronously to cut your bill in half. Ideal for mass document analysis, batch content generation, and data pipelines.

Intelligent model routing

Use 3.5 Flash-Lite ($0.30/1M input) or 3.1 Flash-Lite ($0.25/1M) for high-volume, routine tasks, and reserve 3.1 Pro ($2.00/1M) for complex reasoning. Agent Platform's Model Optimizer automates this via a single meta-endpoint.

Levels of thinking

Gemini 3 models use "dynamic thinking" by default. Control the depth using the parameter to reduce output tokens for tasks that do not require deep reasoning.

Keep an eye on the 200K-token threshold.

Above 200K context tokens, Pro models apply "long context" rates: inputs increase from $2.00 to $4.00 per million tokens, and outputs from $12.00 to $18.00 per million. Design your architecture to stay below this limit.

Intelligent grounding

The 5,000 free monthly Google Search queries are shared across all Gemini 3.x models. If you use Grounding extensively, monitor your usage to avoid charges of $14 per 1,000 queries.

Ready to integrate Gemini into your company?

As a Google Cloud Premier Partner , we help you choose the right platform, design the architecture, and take your generative AI project to production.

Request a free consultation hola@thecloudcollective.es