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Gemini 2.0 Flash

Gemini 2.0 Flash is Google's workhorse model for the agentic era. It delivers low-latency multimodal output, including natively generated images and steerable text-to-speech (TTS) audio, alongside native tool use and a Multimodal Live API for real-time streaming.

File InputTool UseVision (Image)Web Search
index.ts
import { streamText } from 'ai'


const result = streamText({
  model: 'google/gemini-2.0-flash',
  prompt: 'Why is the sky blue?'
})
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Frequently Asked Questions

  • What makes Gemini 2.0 Flash different from 1.5 Flash?

    Gemini 2.0 Flash adds native multimodal output (images and steerable TTS audio), native tool use (Google Search, code execution, user-defined functions), and the Multimodal Live API for real-time streaming, while maintaining similar latency to 1.5 Flash and outperforming 1.5 Pro on key benchmarks.

  • What is the Multimodal Live API and does AI Gateway support it?

    The Multimodal Live API is a streaming interface released alongside 2.0 Flash. It supports real-time audio and video input with combined tool use. Check the AI Gateway documentation and your provider in vertex, google for current Live API support.

  • Can Gemini 2.0 Flash generate images and audio in the same response as text?

    Yes. Gemini 2.0 Flash produces natively generated images and steerable text-to-speech audio alongside text in a single response, without requiring separate generation calls.

  • How does the context window of 1.0M tokens affect prompt construction?

    With 1.0M tokens, you can pass entire codebases, long PDF documents, hours of transcripts, or extended conversation histories in a single context, eliminating the need to chunk or summarize inputs for most practical workloads.

  • What native tools can Gemini 2.0 Flash call?

    Gemini 2.0 Flash supports Google Search, code execution, and third-party user-defined functions natively, enabling it to fetch live information, run and test code, and call external APIs within a single inference pass.

  • Is Gemini 2.0 Flash suitable for building Project Astra-style universal assistant experiences?

    Yes. Google uses Gemini 2.0 Flash as the foundation for Project Astra prototypes, which rely on its multimodal reasoning, native tool use, low latency, and multi-language conversational capabilities.

  • How does Zero Data Retention work with this model through AI Gateway?

    Yes, Zero Data Retention is available for this model. ZDR on AI Gateway applies to direct gateway requests; BYOK flows aren't covered. See https://vercel.com/docs/ai-gateway/capabilities/zdr for details.

  • What safety measures are built into Gemini 2.0 Flash?

    Gemini 2.0 Flash uses reinforcement learning to critique its own responses and improve handling of sensitive prompts. Google also runs automated red teaming to assess risks including indirect prompt injection attacks.