Google Gemini

Connect Google Gemini to use Google’s AI models for text generation and analysis in your workflows.

How to set up Google Gemini

Authentication

Google Gemini uses API key authentication:

1. Go to Google AI Studio
2. Sign in with your Google account
3. Create an API key
4. Copy the API key and paste it in Cargo when connecting

Google Gemini actions

Instruct

Generate text responses using Google’s Gemini models.

Required fields:

• Model: Select the Gemini model
• Prompt: Your instruction or question

Available models:

Model	Description	Context Window
gemini-3-pro-preview	Latest generation with advanced reasoning	2M tokens
gemini-2.5-flash	Fast, cost-efficient for diverse tasks	1M tokens
gemini-2.5-pro	Most capable for complex reasoning	2M tokens
gemini-2.0-flash	Fast multimodal from 2.0 generation	1M tokens
gemini-1.5-flash	Efficient, optimized for speed	1M tokens
gemini-1.5-pro	Advanced with large context	2M tokens

Advanced settings:

• System prompt: Set context for the model’s behavior
• Maximum output tokens: Limit response length
• Temperature: Control randomness (0-2, default 1)
• With Google Search: Enable real-time information retrieval

Output options:

• Text: Plain text response
• JSON object: Unstructured JSON output
• JSON schema: Structured output matching your schema

Use cases

• Lead qualification: Analyze lead data and provide scoring insights
• Email generation: Create personalized outreach at scale
• Data parsing: Extract structured data from unstructured sources
• Translation: Translate content for international campaigns
• Summarization: Condense long documents or conversations

Credits and pricing

Costs vary by model (per 1,000 tokens):

Model	Standard	With Google Search
gemini-3-pro-preview	0.2 credits	0.2 + 1 fixed
gemini-2.5-pro	0.15 credits	0.15 + 1 fixed
gemini-2.5-flash	0.03 credits	0.03 + 1 fixed
gemini-2.0-flash	0.01 credits	0.01 + 1 fixed
gemini-1.5-pro	0.1 credits	0.1 + 1 fixed
gemini-1.5-flash	0.01 credits	0.01 + 1 fixed

Rate limits

Model	Requests per minute
gemini-3-pro-preview	1,000
gemini-2.5-flash	15,000
gemini-2.5-pro	1,000
gemini-2.0-flash	15,000
gemini-1.5-flash	15,000
gemini-1.5-pro	2,000

Best practices

• Use Flash models for simple, high-volume tasks
• Use Pro models for complex reasoning and analysis
• Enable Google Search for questions requiring current information
• Define JSON schemas for consistent, structured outputs
• Adjust temperature based on task (lower for factual, higher for creative)
• Leverage the large context windows for processing lengthy documents