Technology · AI

Gemini

Google's frontier model — native multimodality, the biggest context windows, and a home-field advantage on Google Cloud.

Made by
Google DeepMind
First release
2023
Interface
API · Vertex AI · Gemini app
In our stack since
2024
In plain English

What it is, and why we use it.

Gemini is Google DeepMind's model family, built multimodal from the ground up: video, audio, images and text in one model rather than bolted-on adapters. Its context windows are among the largest in the industry, and through Vertex AI it plugs directly into the Google Cloud and Workspace estate many enterprises already run on.

We reach for Gemini when the input isn't text: analysing video walkthroughs, processing audio, reading mixed-media archives. For clients on Google Cloud, Vertex AI keeps data inside their existing trust boundary — which often decides the choice before benchmarks do.

Key differences

Gemini vs ChatGPT / GPT vs Claude.

Gemini against the two labs it's usually shortlisted with — where scale and multimodality win, and where they don't.

DimensionGeminiChatGPT / GPTClaude
Made byGoogle DeepMindOpenAIAnthropic
Strongest atVideo/audio understanding, giant contextEcosystem breadth and consumer reachAgentic coding and careful reasoning
Context windowLargest advertised in the industryStrongExcellent recall at long lengths
MultimodalNative — video, audio, image, text in oneBroad — strong vision and voice modesVision-capable, text-first
Enterprise storyVertex AI + Workspace integrationAzure OpenAIBedrock / Vertex availability
PricingAggressive at the mid-tierPremium, fallingPremium

Gemini wins when

  • The product ingests video, audio or massive document sets
  • You're already a Google Cloud / Workspace shop
  • Mid-tier price-performance matters at scale

ChatGPT / GPT wins when

  • You need the broadest tool and integration ecosystem
  • Consumer familiarity is a product feature
  • Azure is the mandated cloud

Claude wins when

  • Production code generation is the core workload
  • Agent reliability over long tasks is critical
  • Instruction-following precision matters most
Our take

Gemini is our pick for multimodal-heavy products and Google-committed enterprises. For pure code and agent work we still measure it against Claude — and routing the right task to the right model is exactly the kind of engineering we're paid for.

Thinking about Gemini?

Tell us what you're building — we'll tell you honestly whether Gemini is the right tool for it.