Google Gemini

What is Google Gemini

Google Gemini is best viewed as an ecosystem rather than a single assistant. It includes the Gemini user experience, Gemini inside Google products, and the Google Cloud stack for developers and enterprises. That matters because buyers can start with productivity use cases and expand into grounded search, agent building, model hosting, multimodal inference, and data workflows without leaving Google’s infrastructure.

Google’s route into this market runs from its earlier Bard assistant and years of foundation-model research into the Gemini era, where the company unified consumer AI, developer APIs, and Google Cloud deployment under one family. That history matters because Gemini is now less a single chatbot and more a full Google AI stack that spans search, productivity, and enterprise infrastructure.

Core offerings

• Gemini for everyday chat, drafting, search-style answers, and workspace productivity.
• Google Cloud’s Agent Platform for model access, orchestration, and enterprise deployment.
• Model Garden, which Google describes as a single place to discover 200+ models from Google and partners.
• Strong grounding options through Google Search, enterprise data, and Google Maps integrations.
• Broad multimodal support across text, image, video, and audio.

Pricing

Google’s pricing varies by surface. On the Google Cloud side, current public pricing shows Gemini 3.1 Pro Preview at US$1 per million input tokens and US$6 per million output tokens in Flex/Batch pricing at up to 200K input tokens. Gemini 3.5 Flash is listed from US$0.75 per million input tokens on the global endpoint, and grounding with your data is listed at US$2.50 per 1,000 prompts.

Model footprint

For enterprises, the practical headline is Google’s 200+ model catalog in Model Garden plus Gemini-first models for high-volume production work. If you want optionality inside one cloud account, Gemini scores well.

Why select Google Gemini

Gemini is attractive when your team already runs on Google Workspace or Google Cloud, or when search, grounding, and multimodal workflows are central to the use case. It also suits buyers who want a large catalogue instead of committing to one frontier lab.

Official sources: Google Cloud Gemini pricing, Google Cloud Gemini product pages.

Current models

Google’s public model catalogue is spread across AI Studio and Cloud surfaces, so the table below focuses on the current Gemini Developer API models with clearly published public specs.