Gemini — Google's multimodal AI model family

Gemini is Google's flagship AI model family — the engine behind Gemini app, Google Workspace AI features, Search's AI Overviews, and Vertex AI for enterprise.

What Gemini actually is

Gemini is Google's flagship AI model family, announced in December 2023 as a successor to the earlier Bard product and to LaMDA, PaLM, and PaLM 2 models. The family includes Gemini Nano (on-device for Pixel and Android), Gemini Flash (fast, low-cost), Gemini Pro (mid-tier), and Gemini Ultra (top-tier reasoning and multimodal). Google rebranded Bard to Gemini in February 2024 to align consumer product naming with model naming.

Google's competitive position in AI: Google invented the Transformer architecture ("Attention is All You Need," 2017), invested in DeepMind (acquired 2014), runs the largest distributed compute infrastructure in the world, and integrates Gemini into every Google product surface (Search, Workspace, Android, Chrome, YouTube, Maps). DeepMind and Google Brain merged into Google DeepMind in April 2023 under Demis Hassabis as the unified AI research division. By 2026, Gemini is one of the three top-tier LLMs (with ChatGPT and Claude) and arguably the most-integrated AI across consumer products.

Gemini product surface

GEMINI APP CONSUMER WEB + MOBILE WORKSPACE AI GMAIL + DOCS + SHEETS AI OVERVIEWS GOOGLE SEARCH SYNTHESIS VERTEX AI ENTERPRISE API GCP FIG. 01 RGM® · BLUEPRINT

FIG. 01 — Gemini product surface

Gemini's surface in 2026: the standalone Gemini app (consumer chat at gemini.google.com plus iOS/Android apps), Gemini Advanced (paid tier at $20/month for Gemini Ultra access), Workspace AI (Gemini integrated into Gmail, Docs, Sheets, Slides, Meet, Drive), Search AI Overviews (Gemini synthesizes search results), Android and Pixel integration (Gemini Nano on-device), Chrome integration (sidebar Gemini), Vertex AI (enterprise API on Google Cloud Platform), Gemini Code Assist (developer code completion), and NotebookLM (Google's standout AI-augmented research and note-taking product).

Marketing use cases

Gemini in marketing is most-valuable for: Workspace-native AI (Gemini in Docs and Gmail for drafting, in Sheets for data analysis, in Slides for deck building — particularly powerful because the workflow stays inside Google Workspace), Search optimization (Gemini-powered AI Overviews are the most-trafficked AI search product — see our GEO Ultimate Guide), NotebookLM-powered research (uploading source documents and asking Gemini to synthesize), and multimodal analysis (Gemini's image and video understanding capabilities outpace ChatGPT on many multimodal tasks).

Gemini's weaker areas in marketing: long-form content drafting (Claude typically produces better written output), conversational ideation (ChatGPT's pattern matching is faster), and creative ideation (subjective but most operators prefer Claude or ChatGPT for first-pass creative work). The right pattern is multi-LLM — see our ChatGPT coverage for the full multi-LLM stack rationale.

AI Overviews — Gemini's biggest marketing impact

Gemini powers Google's AI Overviews — the most-trafficked AI search product in the world, handling 5-6 billion AI-summarized queries per day across the markets where it has rolled out. For brands, optimizing for AI Overview citation is the single highest-leverage AI-related SEO work in 2026. See our Generative Engine Optimization Ultimate Guide for the full discipline, including citation patterns, content structure, and the Google-Extended crawler considerations.

Citation in AI Overviews correlates with classical SEO rank but with distinct ranking weights — answer-paragraph format, original data, and structured data lift citation probability above what classical ranking would predict.

RGM Experts Say

We allow Google-Extended (the crawler that feeds Gemini training and AI Overview retrieval) in robots.txt for every client. Blocking it means losing eligibility for AI Overview citation, which is a substantial traffic source. The training-data tradeoff is real but secondary — the citation traffic is more valuable than the marginal cost of contributing to training data, and the contribution is non-exclusive anyway.

Vertex AI — the enterprise API

Vertex AI is Google Cloud's enterprise AI platform — Gemini API access plus the broader AI/ML platform (Model Garden, AutoML, MLOps tooling). Pricing varies by model: Gemini Flash at $0.075/$0.30 per million input/output tokens (the cheapest top-tier model on the market in 2026); Gemini Pro at $1.25/$5.00; Gemini Ultra at premium tiers. Enterprise considerations: data residency, VPC controls, SSO, audit logging, all standard.

For marketing teams building custom AI features, Vertex AI competes with OpenAI API, Anthropic's Claude API, and AWS Bedrock. The choice usually depends on existing cloud commitments — GCP-heavy organizations default to Vertex; AWS-heavy organizations default to Bedrock; mixed-cloud organizations evaluate per-task.

Gemini vs ChatGPT vs Claude — quick framework

Quick decision framework: use Gemini for Google Workspace-integrated workflows, multimodal analysis, and anything that benefits from real-time search grounding. Use ChatGPT for broad ecosystem integrations, Custom GPTs, and Operator agentic workflows. Use Claude for long-form drafting, analytical writing, and computer-use agentic workflows. Most marketing teams running serious AI workflows pay for all three subscriptions (~$60/month per seat) and route work by task fit.

How we work with this technology

We use the tools that fit the job. If our approach feels aligned with your business, apply for an engagement.