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[ MODEL COMPARISON ]

Compare gemini-2.5-flash-image with other models

Select another model to compare pricing, limits, and capabilities with gemini-2.5-flash-image.

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Models
Google Gemini logogemini-2.5-flash-image
gemini
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Context Length
33K
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Max Output
33K
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Input Cost
$0.30/M
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Output Cost
$2.50/M
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Mode
Image Generation
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Max Input Tokens
33K
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Max Tokens
33K
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Supported Endpoints
/v1/chat/completions, /v1/completions, /v1/batch
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Provider
Google Gemini
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Tool Choice
Yes
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Response Schema
Yes
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Parallel Function Calling
Yes
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Prompt Caching
Yes
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System Messages
Yes
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Comparison Insights

Comprehensive analysis based on the latest model metadata from the comparison table above.

What should I know about gemini-2.5-flash-image?

Overview

  • gemini-2.5-flash-image is a image generation model provided by Google Gemini.
  • The model supports a 33K-token context window, suitable for moderate-sized documents and multi-turn conversations.

Pricing

  • Input processing costs $0.30 per million tokens.
  • Output generation costs $2.50 per million tokens.
  • Image generation costs $0.0390 per image.

Output Capabilities

  • The model can generate up to 33K tokens in a single response.

Availability

  • Available through the following endpoints: /v1/chat/completions, /v1/completions, /v1/batch.
What capabilities does gemini-2.5-flash-image support?
  • Supports function calling, enabling integration with external tools and APIs for extended functionality.
  • Includes vision capabilities to process and analyze images alongside text inputs.
  • Provides web search integration for accessing real-time information and current data.
  • Allows explicit tool selection, giving developers fine-grained control over function execution.
  • Supports structured response schemas for consistent, predictable output formatting.
  • Enables parallel function calling to execute multiple operations simultaneously for improved efficiency.
  • Implements prompt caching to reduce costs and latency for repeated or similar queries.
  • Supports system messages for customizing model behavior and setting operational parameters.