Gemini Series by Google
The Gemini Series, developed by Google DeepMind, is a family of multimodal large language models optimized for complex reasoning, multimodal understanding, adaptive thinking, and advanced coding tasks. Gemini models support a range of inputs including text, images, audio, and video, designed for diverse enterprise and real-time agentic AI applications.
Current Models in the Gemini Series:
Gemini 2.5 Pro Preview (gemini-2.5-pro-preview-03-25):
Optimized for enhanced thinking and reasoning, multimodal understanding, and advanced coding tasks.Gemini 2.5 Flash Preview (gemini-2.5-flash-preview-04-17):
Designed for adaptive thinking, delivering strong cost efficiency with multimodal input support.Gemini 2.0 Flash (gemini-2.0-flash):
Supports next-generation features including real-time streaming and multimodal generation (text, images, and audio coming soon), optimized for speed and responsive thinking.Gemini 2.0 Flash-Lite (gemini-2.0-flash-lite):
Optimized for cost efficiency and low latency, suitable for high-volume applications.Gemini 2.0 Flash Live (gemini-2.0-flash-live-001):
Specialized for low-latency, bidirectional voice and video interactions.Gemini 1.5 Pro (gemini-1.5-pro):
Tailored for complex reasoning tasks requiring higher intelligence and cognitive capabilities.Gemini 1.5 Flash (gemini-1.5-flash):
Offers fast and versatile performance for diverse tasks.Gemini 1.5 Flash-8B (gemini-1.5-flash-8b):
Designed for tasks requiring high throughput at a lower computational intensity.Gemini Embedding (gemini-embedding-exp):
Generates text embeddings to measure semantic relatedness between text strings.Imagen 3 (imagen-3.0-generate-002):
Advanced text-to-image generation model producing high-quality images.Veo 2 (veo-2.0-generate-001):
High-quality video generation model supporting text and image inputs.
Key Attributes:
Multimodal Capabilities: Supports seamless integration of text, images, audio, and video inputs.
Advanced Reasoning & Coding: Optimized for complex tasks including coding assistance, debugging, and logical problem-solving.
Adaptive Thinking & Real-time Interaction: Designed for dynamic interactions and responsive reasoning across multiple modalities.
Low Latency & Cost Efficiency: Variants tailored specifically for cost-sensitive and latency-critical applications.
Enterprise Integration: Available via Google AI Studio and Vertex AI for scalable enterprise deployment.
Example Use Cases:
Developing advanced coding assistants and debugging tools (Gemini 2.5 Pro Preview).
Real-time customer support chatbots with multimodal input capabilities (Gemini 2.0 Flash).
Cost-effective, high-volume deployments for voice or text-based interactions (Gemini 2.0 Flash-Lite).
Low-latency voice and video interactions for virtual meetings and customer engagement (Gemini 2.0 Flash Live).
Generating high-quality images and videos from textual descriptions (Imagen 3 and Veo 2).