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 3.8 Flash
3 credits • Gemini’s newest Flash model, built for long-horizon engineering and autonomous agents.
- 1M context window
- Exceptional reasoning (reasoning model)
- Speed: Fast • Cost: Medium
- Vision: images supported
Gemini 3.7 Flash
2 credits • The newest Gemini Flash model, with a 1M-token context window and native multimodal input.
- 1.05M context window
- Exceptional reasoning (reasoning model)
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gemini-3.7-flash
Gemini 3.6 Flash
2 credits • Balances speed with intelligence for strong performance on agentic and multimodal tasks.
- 1M context window
- Excellent reasoning (reasoning model)
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gemini-3.6-flash
Gemini 3.5 Flash
3 credits • Most intelligent Gemini model for sustained frontier performance on agentic and coding tasks.
- 1M context window
- Exceptional reasoning (reasoning model)
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gemini-3.5-flash
Gemini 3.5 Flash Lite
1 credit • The fastest, most cost-effective Gemini 3.5 model for high-throughput execution.
- 1M context window
- Good reasoning (reasoning model)
- Speed: Very_fast • Cost: Very_low
- Vision: images supported
- Model id:
gemini-3.5-flash-lite
Gemini 3.1 Flash Lite
1 credit • Frontier-class performance at a fraction of the cost, optimized for low latency and high-volume tasks.
- 1M context window
- Good reasoning (reasoning model)
- Speed: Very_fast • Cost: Very_low
- Vision: images supported
- Model id:
gemini-3.1-flash-lite
Gemini 3.1 Pro
3 credits • Reasoning-first Gemini model for complex agentic workflows and coding, with adaptive thinking.
- 1M context window
- Exceptional reasoning (reasoning model)
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
gemini-3.1-pro-preview
Gemini 3 Flash
1 credit • The latest Gemini 3 Flash model in preview, optimized for speed and efficiency while delivering strong reasoning and language capabilities.
- 1M context window
- Excellent reasoning (reasoning model)
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gemini-3-flash-preview
Gemini 2.5 Flash
1 credit • A fast and capable model in the Gemini 2.5 series, balancing speed and reasoning performance for production use.
- 1M context window
- Excellent reasoning (reasoning model)
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gemini-2.5-flash
Gemini 2.5 Flash Lite
1 credit • A lightweight, cost-efficient variant of Gemini 2.5 Flash, optimized for low latency and basic tasks.
- 1M context window
- Good reasoning (reasoning model)
- Speed: Very_fast • Cost: Very_low
- Vision: images supported
- Model id:
gemini-2.5-flash-lite
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
Next Steps
Model Comparison
Compare all providers
Reasoning Models
Learn about Flash Thinking
Bring Your Own Key
Use your Google AI API key
SDK Reference
Full API documentation