LightweightGoogle

Gemini 2.0 Flash

Gemini 2.0 Flash is Google's lightweight multimodal model with text, image, video, and audio capabilities in a 1M token context window.

Context 1.0M
Tier Lightweight
Knowledge Aug 2024
Tools Supported
Modalities text, image, video, audio
Input from
$0.075 / 1M tokens
across 2 providers

API Pricing

Cheapest on Google Cloud 14% below avg
ProviderInput / 1MOutput / 1MUpdated
$0.075$0.3004/12/2026
$0.100$0.4004/14/2026

Prices updated daily. Last check: 4/14/2026

Model Details

General

Creator
Google
Family
Gemini
Tier
Lightweight
Context Window
1.0M
Knowledge Cutoff
Aug 2024
Modalities
Text, Image, Video, Audio

Capabilities

Tool Calling
Yes
Open Source
No
Subtypes
Chat Completion

Strengths & Limitations

  • Supports four modalities: text, image, video, and audio input
  • 1 million token context window for processing large documents and conversations
  • Tool calling support with structured function execution
  • Knowledge cutoff of August 2024 provides relatively current information
  • Lightweight architecture designed for fast inference speeds
  • Multimodal capabilities in a single model reduce integration complexity
  • Proprietary model with no open-source weights available
  • Lightweight tier may have reduced reasoning capabilities compared to Pro models
  • Limited benchmark data available for performance comparison
  • Newer model with less real-world testing than established alternatives

Key Features

1 million token context window
Multimodal input (text, image, video, audio)
Tool calling with function execution
Chat completion interface
Streaming response support
Batch processing capabilities
JSON mode for structured outputs

About Gemini 2.0 Flash

Gemini 2.0 Flash is Google's lightweight multimodal model in the Gemini family, positioned as a fast and efficient option below the flagship Gemini Pro models. It represents the second generation of the Flash tier, designed for high-throughput applications requiring multimodal understanding. The model supports text, image, video, and audio inputs with a 1 million token context window, enabling processing of long documents, extended conversations, and large multimedia files. It includes tool calling capabilities for function execution and API integrations. With a knowledge cutoff of August 2024, it has relatively current training data compared to some competing models. Gemini 2.0 Flash is suited for applications requiring fast multimodal processing at scale, such as content analysis, customer support automation, and document understanding workflows. As a lightweight model, it trades some capability for speed and efficiency compared to larger models in the Gemini family.

Common Use Cases

Gemini 2.0 Flash is designed for high-volume applications requiring fast multimodal processing, including content moderation across text, image, and video, customer support chatbots with document and image understanding, automated document analysis workflows, and real-time multimedia content analysis. Its lightweight architecture and broad modality support make it suitable for applications where speed and multimodal capability are prioritized over maximum reasoning performance, such as content classification, media processing pipelines, and interactive applications requiring quick responses across multiple input types.

Frequently Asked Questions

How much does Gemini 2.0 Flash cost per million tokens?

Gemini 2.0 Flash pricing varies by provider and input type (text vs image/video/audio tokens). Check the pricing table above for current rates across all available providers.

What is Gemini 2.0 Flash best used for?

Gemini 2.0 Flash excels at high-volume multimodal applications requiring fast processing of text, images, video, and audio. It's well-suited for content analysis, customer support automation, document understanding, and real-time multimedia processing where speed is prioritized over maximum reasoning capability.

How does Gemini 2.0 Flash compare to other lightweight models?

Gemini 2.0 Flash distinguishes itself with native support for four modalities (text, image, video, audio) in a single model and a large 1 million token context window. Most lightweight competitors support fewer modalities or have smaller context windows, though specific performance will depend on your use case and the types of inputs you're processing.