Google Models

Gemini Omni 1.1 Flash (Preview) is a multimodal model designed for video, image, and text tasks. It is optimized for video generation, offering video output alongside text responses in a single model.

Gemini Omni Flash (Preview) is a multimodal model designed for video, image, and text tasks. It is optimized for video generation, offering video output alongside text responses in a single model

Gemini Embedding 2 is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It supports input context up to 8,192 tokens and flexible output dimensions from 128 to 3,072 (recommended: 768, 1536, or 3,072). Designed for cross-modal similarity — you can embed a text query and retrieve the most relevant images, or vice versa — making it well-suited for multimodal search, recommendation, and document understanding pipelines.

Gemma 4 31B IT is an instruction-tuned multimodal open model from Google DeepMind with a 256K context window, designed for reasoning, coding, agentic workflows, and image understanding. It accepts text and image inputs and generates text output, with native tool calling and configurable thinking modes for long-context assistant experiences.

Gemini 3.7 Flash is Google’s efficient multimodal model designed for coding and agentic workflows. It improves code generation, web application development, tool use, and reliability in complex multi-step tasks while supporting text, image, audio, and video inputs. With a 1-million-token context window, up to 64,000 tokens of output, and adjustable reasoning levels, it is well suited for coding agents, enterprise automation, complex document analysis, and large-scale multimodal applications.

Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, "thinking" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the Reasoning API parameter to selectively trade off cost for intelligence.

Nano Banana Pro is an AI image generation model that is a significant upgrade from its predecessor, built on Google's Gemini 3 Pro. It promises to move beyond simple pattern matching to a more reasoning-driven system with improved physics understanding, text rendering, and image consistency. Key features include faster processing, native 2K resolution, and the ability to edit existing images with greater control, aiming to produce more reliable and professional-grade results.

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is Google's fastest, most cost-efficient Gemini image model, built for high-velocity developer pipelines and rapid-fire visual exploration. It delivers text-to-image generation in roughly 4 seconds — about 2.7× faster than Gemini 3.1 Flash Image — while keeping the character consistency, precise editing, and real-world knowledge of the Nano Banana family.

A single drop-in API handles text-to-image, image editing, and multi-image composition. As a multimodal model it also returns text alongside images. Outputs are generated at 1K resolution across 14 aspect ratios and carry an invisible SynthID watermark so they can be identified as AI-generated.

Positioned as the best balance of quality and speed in the Nano Banana 2 line, it lets you generate thousands of images at a fraction of the cost of heavier production models — ideal for prototyping, real-time apps, and visual workflows at scale.

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and less hedging, while reducing token use and the number of model calls needed to complete a task.

Gemini 3.5 Flash-Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at a fraction of the compute cost. Supports multimodal input including text, images, and video (up to 60s at 1fps). Features a 256K token context window, native function calling, configurable thinking/reasoning mode, and structured output support. Released under Apache 2.0.

Designed for speed and efficiency, the Gemini 3.1 Flash Image generation model is effective for quick, interactive responses and high throughput.

Gemini 3.8 Flash is Google’s most intelligent workhorse model yet, delivering major gains over 3.7 Flash in software engineering, agentic workflows, and multi-step reasoning for specialized domains. It approaches the quality of higher-cost frontier models while still offering configurable effort levels for balancing performance and token efficiency.

Gemini 3.8 Flash TTS is a text-to-speech model from Google and the successor to Gemini 3.1 Flash TTS Preview. It is the creative tier of the 3.8 TTS family, suited for narration, character work, and multi-speaker dialogue where voice fidelity, acting nuance, and regional dialect coverage matter more than latency.

Gemini 3.8 Flash Lite TTS is a text-to-speech model from Google and the fast, high-throughput member of the 3.8 TTS family alongside Gemini 3.8 Flash TTS. It is suited for conversational voice-agent pipelines, high-volume read-aloud, and voice replication workloads where latency and cost matter more than maximum expressiveness.

Gemini Nano Banana 2.1 is an upgraded multimodal reasoning image model for production-grade image generation and editing, with stronger prompt adherence, multi-reference editing, and improved visual fidelity. It understands text, images, video, and PDF inputs, supports interleaved text and image generation, and can reason over complex spatial and compositional instructions before generating images. The model also supports grounding with Google Search and Google Image Search for better long-tail entity recognition, visual understanding, and output accuracy.

Gemini 4 Argon is a frontier model from Google DeepMind, released on September 30, 2026. It is the first model in the Gemini 4 series and uses a new naming scheme. It is strong in coding, financial research, legal drafting, and autonomously patching cybersecurity vulnerabilities. It accepts text, image, video, and file inputs and has a 1-million-token context window. On benchmarks, it scores 77.9% on DeepSWE v1.1, ahead of Claude Opus 5.5 and GPT-6 Astra, and ranks first on the Vals Index with 68.90%.

Gemini 3.5 Flash is engineered specifically to power high-speed, cost-efficient, and complex developer and agentic workflows. It brings powerful multi-step reasoning capabilities to a highly optimized, low-latency framework, making it highly effective for running massive reasoning loops at scale.

Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling.

Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter, as described in the documentation.

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy and nuanced context handling. Gemini 2.5 Pro achieves top-tier performance on multiple benchmarks, including first-place positioning on the LMArena leaderboard, reflecting superior human-preference alignment and complex problem-solving abilities.

Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image generation, edits, and multi-turn conversations.

Gemini 3 Flash Preview is a low-latency model in the Gemini 3 family, optimized for fast, high-throughput inference. It retains the core multimodal and reasoning capabilities of Gemini 3 while prioritizing responsiveness and execution efficiency. Built on the same architecture as Gemini 3 Pro, Gemini 3 Flash Preview supports native multimodal inputs—including text, images, and audio—and incorporates the improved reasoning and long-context handling introduced in the Gemini 3 generation. It is designed for real-time and scalable workloads where latency and cost efficiency are primary considerations.

Gemini 3.1 Pro is the next generation in the Gemini series of models, a suite of highly-capable, natively multimodal, reasoning models. Gemini 3 Pro is now Google’s most advanced model for complex tasks, and can comprehend vast datasets, challenging problems from different information sources, including text, audio, images, video, and entire code repositories

Gemini 3.1 Flash-Lite is Google's most cost-efficient Gemini model, optimized for low latency use cases for high-volume, cost-sensitive LLM traffic. It provides a significant quality increase over Gemini 2.0/2.5 Flash-Lite models, matching Gemini 2.5 Flash performance across key capability areas.

Gemini 3.1 Flash TTS Preview is a text-to-speech model from Google, and a substantial generational step up from Gemini 2.5 Flash TTS. It takes text input and produces audio output across 70+ languages — nearly 3× the language coverage of its predecessor.

Veo 3.1 Fast is a speed-optimized variant of Google DeepMind's flagship video generation model. It is designed to generate high-quality video significantly faster and at a lower cost than the standard Veo 3.1 Quality model, making it ideal for rapid prototyping and high-volume content creation.

Veo 3.1 is Google's state-of-the-art model for generating high-fidelity, 8-second 720p, 1080p or 4k videos featuring stunning realism and natively generated audio. You can access this model programmatically using the Gemini API. To learn more about the available Veo model variants, see the Model Versions section.

Veo 3.1 Lite is Google DeepMind's most cost-efficient AI video generation model, released on March 31, 2026. It is designed to provide professional-grade video capabilities at a significantly lower price point, making it ideal for developers and content teams who need to scale high-volume video production