Case study: Gemini
定义
Gemini is Google’s 家族 LLMs with native multimodal support: text, image, audio, and video in one model. It succeeds earlier Google models (例如 BART in the encoder-decoder line) and is offered in multiple scale tiers (Nano, Pro, Ultra) for different latency and capability trade-offs.
Gemini is trained and deployed across Google products (Search, Workspace, Vertex AI, Android). Use case: chat, multimodal understanding and generation, coding, and agent-style tool use.
工作原理
多模态输入（文本、图像、音频、视频）在统一的 transformer 中编码和融合tack. The decoder generates text (or structured output) conditioned on all modalities. Scale tiers: smaller models (例如 Nano) for edge and on-device; larger (Pro, Ultra) for maximum capability in the cloud. Integration: same models power Gemini in Search, Workspace, and Vertex AI APIs. Prompt engineering and RAG or tools extend use in applications.
应用场景
Gemini fits when you need multimodal understanding or generation and optional integration with Google’s stack.
- Chat and assistants with image, document, or video understanding
- Multimodal search, summarization, and content generation
- Coding and 推理 via API or Google products
外部文档
- Google AI – Gemini — API and overview
- Google – Gemini models — Model tiers and capabilities
另请参阅
- LLMs
- Multimodal AI
- BART — Predecessor in the encoder-decoder line