Overview
Google’s Gemini models offer industry-leading context windows (up to 2 million tokens), exceptional multimodal capabilities, and strong performance across text, code, and reasoning tasks.Available Models
Gemini 3 Pro Preview (Latest)
Gemini 3 Pro Preview
5 credits • Cutting-edge preview model
- 2,000,000 token context window (largest available)
- Exceptional reasoning and contextual understanding
- Speed: Medium • Cost: High
- Best for: Research, massive documents, advanced R&D
Gemini 2.5 Series (Stable)
Gemini 2.5 Pro
3 credits • Most advanced stable model
- 2,000,000 token context window
- Exceptional reasoning and accuracy
- Speed: Slow • Cost: High
- Best for: Complex reasoning, long documents
Gemini 2.5 Flash
2 credits • Fast and capable
- 1,000,000 token context window
- Excellent reasoning with speed
- Speed: Fast • Cost: Medium
- Best for: Production applications
Gemini 2.5 Flash Lite
1 credit • Ultra-fast and efficient
- 1,000,000 token context window
- Good reasoning at lowest cost
- Speed: Very Fast • Cost: Very Low
- Best for: High-volume, simple tasks
Gemini 2.0 Flash Thinking
3 credits • Reasoning model
- 1,000,000 token context window
- Explicit thinking process for analysis
- Speed: Medium • Cost: Medium
- Reasoning model for problem-solving
Setup
Using BoostGPT-Hosted API Keys
1
Select Gemini Model
In your BoostGPT dashboard, select any Gemini model when creating or configuring your bot.
2
Choose Your Model
- Gemini 2.5 Flash: Best for most production use cases
- Gemini 2.5 Pro: When you need massive 2M context
- Gemini 2.5 Flash Lite: High-volume, cost-sensitive
- Gemini 2.0 Flash Thinking: Complex reasoning tasks
Using Your Own Google AI API Key
- Dashboard Setup
- Core SDK
- Router SDK
1
Navigate to Integrations
Go to app.boostgpt.co and select Integrations
2
Select Google AI
Find and click on the Google provider
3
Add API Key
Get your API key from Google AI StudioEnter the API key and select which agents will use it
4
Save Configuration
Click save to apply your custom API key
Model Selection Guide
Gemini 2.5 Flash - Production Workhorse
Gemini 2.5 Flash - Production Workhorse
Best for:
- Production chatbots and customer support
- General-purpose applications
- Fast responses with strong reasoning
- 1M context for long conversations
Gemini 2.5 Pro - Maximum Context
Gemini 2.5 Pro - Maximum Context
Best for:
- Analyzing entire codebases
- Processing very long documents (books, research papers)
- Multi-turn conversations with full history
- Maximum context retention (2M tokens)
Gemini 2.5 Flash Lite - High Volume
Gemini 2.5 Flash Lite - High Volume
Best for:
- High-volume applications (thousands of requests)
- Simple queries and responses
- Cost-sensitive production
- Quick classifications
Gemini 2.0 Flash Thinking - Reasoning
Gemini 2.0 Flash Thinking - Reasoning
Best for:
- Mathematical problem solving
- Code analysis and debugging
- Multi-step logical reasoning
- Scientific tasks
Gemini 3 Pro Preview - Cutting Edge
Gemini 3 Pro Preview - Cutting Edge
Best for:
- Research and experimentation
- Testing next-generation capabilities
- Maximum context + latest features
Troubleshooting
Slow responses with Pro
Slow responses with Pro
Expected: Pro prioritizes accuracy over speedSolutions:
- Use Flash for faster responses
- Reduce input length when possible
- Add loading indicators
Context length errors
Context length errors
Rare: 1M-2M context handles most casesSolutions:
- Use Pro for maximum 2M context
- Implement message pruning for extreme cases
- Split very large documents
Higher costs than expected
Higher costs than expected
Cause: Long contexts consume many tokensSolutions:
- Use Flash Lite for simple tasks (1 credit)
- Implement context pruning
- Set max_reply_tokens limits
- Monitor token usage in dashboard