Gemini
Google DeepMind's natively multimodal model family, announced December 2023, and the model line behind AI Overviews and AI Mode in Google Search.
Gemini is Google DeepMind's multimodal model family, announced in December 2023, and the model line behind AI Overviews and AI Mode in Google Search. It is natively multimodal: text, images, audio and video are handled by one model rather than by encoders bolted onto a text model.
The line
Gemini 1.0 shipped in Ultra, Pro and Nano sizes, the last of which runs on device. Gemini 1.5 Pro introduced a 1 million token context window in February 2024, later extended to 2 million, which is the step that made whole-corpus prompting practical. Later generations split into Flash variants tuned for latency and cost and Pro variants tuned for capability, with explicit reasoning added in the 2.5 generation.
Where it runs
Gemini is reached through the Gemini app, the Gemini API in Google AI Studio, and Vertex AI for enterprise deployments. The same family powers Google's generative search surfaces, which is why its retrieval behaviour decides AI visibility: what Gemini retrieves and cites in AI Mode determines which pages appear in the answer.
Related concepts
Mentioned in
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Gemini writes better answers when it knows the user is a recognised expert
Tell Gemini you're a known expert and its answers get better. Across 15 topics, blind-rated answers scored 7.8 out of 10 for experts and 5.8 with no name.
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Google sends Knowledge Graph facts to AI Mode as uncited "Biography" search results
AI Mode receives Knowledge Graph biographies of people and companies as search results with no URL. Building on Natzir Turrado and Olivier de Segonzac: 99 QRS providers, 542 result types and 268 query signals in Google Earth's 15 October build.
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New Feature: Grounding Snippet Ablation
The new Ablation tab in DEJAN's Content Optimizer measures how many rank places each sentence of an AI-cited source is worth.
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We Tested an AI for Signs of Inner Experience. Nobody's Home.
Eight behavioural tests on Gemini found no evidence of AI consciousness, though results reveal how the model categorises and judges its own self-concept.
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Gemini 4 Argon - One Step Closer to 'Model as an Employee' Paradigm
Google's Gemini 4 Argon introduces a 1-million-token output limit to support long-horizon autonomous tasks, enterprise benchmarks, and complex code migrations.
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Your 'Gmail' can write code.
Gemini in Gmail drafted Python code to fine-tune a DeBERTa model for sentiment classification, complete with data loading, training loops, and evaluation.
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A free 300M model predicts Gemini's embeddings at 0.83 cosine
Mapping Gemma embeddings to Gemini embeddings via a linear transform recovers entity vector structures with high fidelity without calling the paid API.