Model Selection Guide
Last updated: Feb 5, 2025.
Understanding Context Windows
Think of a context window as your AI assistant's working memory - similar to RAM in a computer. It determines how much information the model can "remember" and process at once during your conversation. This includes:
Your code files and conversations
The assistant's responses
Any documentation or additional context provided
Context windows are measured in tokens (roughly 3/4 of a word in English). Different models have different context window sizes:
Claude 3.5 Sonnet: 200K tokens
DeepSeek Models: 128K tokens
Gemini Flash 2.0: 1M tokens
Gemini 1.5 Pro: 2M tokens
When you reach the limit of your context window, older information needs to be removed to make room for new information - just like clearing RAM to run new programs. This is why sometimes AI assistants might seem to "forget" earlier parts of your conversation.
Cline helps you manage this limitation with its Context Window Progress Bar, which shows:
Input tokens (what you've sent to the model)
Output tokens (what the model has generated)
A visual representation of how much of your context window you've used
The total capacity for your chosen model
This visibility helps you work more effectively with Cline by letting you know when you might need to start fresh or break tasks into smaller chunks.
Model Comparison
LLM Model Comparison for Cline (Feb 2025)
Claude 3.5 Sonnet
$3.00
$15.00
200K
Best code implementation & tool use
DeepSeek R1
$0.55
$2.19
128K
Planning & reasoning champion
DeepSeek V3
$0.14
$0.28
128K
Value code implementation
o3-mini
$1.10
$4.40
200K
Flexible use, strong planning
Gemini Flash 2.0
$0.00
$0.00
1M
Strong all-rounder
Gemini 1.5 Pro
$0.00
$0.00
2M
Large context processing
*Costs per million tokens
Top Picks for 2025
Claude 3.5 Sonnet
Best overall code implementation
Most reliable tool usage
Expensive but worth it for critical code
DeepSeek R1
Exceptional planning & reasoning
Great value pricing
o3-mini
Strong for planning with adjustable reasoning
Three reasoning modes for different needs
Requires OpenAI Tier 3 API access
200K context window
DeepSeek V3
Reliable code implementation
Great for daily coding
Cost-effective for implementation
Gemini Flash 2.0
Massive 1M context window
Improved speed and performance
Good all-around capabilities
Best Models by Mode (Plan or Act)
Planning
DeepSeek R1
Best reasoning capabilities in class
Excellent at breaking down complex tasks
Strong math/algorithm planning
MoE architecture helps with reasoning
o3-mini (high reasoning)
Three reasoning levels:
High: Complex planning
Medium: Daily tasks
Low: Quick ideas
200K context helps with large projects
Gemini Flash 2.0
Massive context window for complex planning
Strong reasoning capabilities
Good with multi-step tasks
Acting (coding)
Claude 3.5 Sonnet
Best code quality
Most reliable with Cline tools
Worth the premium for critical code
DeepSeek V3
Nearly Sonnet-level code quality
Better API stability than R1
Great for daily coding
Strong tool usage
Gemini 1.5 Pro
2M context window
Good with complex codebases
Reliable API
Strong multi-file understanding
A Note on Local Models
While running models locally might seem appealing for cost savings, we currently don't recommend any local models for use with Cline. Local models are significantly less reliable at using Cline's essential tools and typically retain only 1-26% of the original model's capabilities. The full cloud version of DeepSeek-R1, for example, is 671B parameters - local versions are drastically simplified copies that struggle with complex tasks and tool usage. Even with high-end hardware (RTX 3070+, 32GB+ RAM), you'll experience slower responses, less reliable tool execution, and reduced capabilities. For the best development experience, we recommend sticking with the cloud models listed above.
Key Takeaways
Plan vs Act Matters: Choose models based on task type
Real Performance > Benchmarks: Focus on actual Cline performance
Mix & Match: Use different models for planning and implementation
Cost vs Quality: Premium models worth it for critical code
Keep Backups: Have alternatives ready for API issues
*Note: Based on real usage patterns and community feedback rather than just benchmarks. Your experience may vary. This is not an exhaustive list of all the models available for use within Cline.
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