What is a Context Window?
A context window is the maximum amount of text an AI model can process at once. Think of it as the model’s “working memory” - it determines how much of your conversation and code the model can consider when generating responses.
Key Point: Larger context windows allow the model to understand more of your codebase at once, but may increase costs and response times.
 
Quick Reference
| Size | Tokens | Approximate Words | Use Case | 
|---|
| Small | 8K-32K | 6,000-24,000 | Single files, quick fixes | 
| Medium | 128K | ~96,000 | Most coding projects | 
| Large | 200K | ~150,000 | Complex codebases | 
| Extra Large | 400K+ | ~300,000+ | Entire applications | 
| Massive | 1M+ | ~750,000+ | Multi-project analysis | 
 
Model Context Windows
| Model | Context Window | Effective Window* | Notes | 
|---|
| Claude Sonnet 4.5 | 1M tokens | ~500K tokens | Best quality at high context | 
| GPT-5 | 400K tokens | ~300K tokens | Three modes affect performance | 
| Gemini 2.5 Pro | 1M+ tokens | ~600K tokens | Excellent for documents | 
| DeepSeek V3 | 128K tokens | ~100K tokens | Optimal for most tasks | 
| Qwen3 Coder | 256K tokens | ~200K tokens | Good balance | 
 
*Effective window is where model maintains high quality
What Counts Toward Context
- Your current conversation - All messages in the chat
 
- File contents - Any files you’ve shared or CodinIT has read
 
- Tool outputs - Results from executed commands
 
- System prompts - CodinIT’s instructions (minimal impact)
 
Optimization Strategies
1. Start Fresh for New Features
/new - Creates a new task with clean context
 
Benefits:
- Maximum context available
 
- No irrelevant history
 
- Better model focus
 
2. Use @ Mentions Strategically
Instead of including entire files:
@filename.ts - Include only when needed 
- Use search instead of reading large files
 
- Reference specific functions rather than whole files
 
3. Enable Auto-compact
CodinIT can automatically summarize long conversations:
- Settings → Features → Auto-compact
 
- Preserves important context
 
- Reduces token usage
 
Context Window Warnings
Signs You’re Hitting Limits
| Warning Sign | What It Means | Solution | 
|---|
| ”Context window exceeded” | Hard limit reached | Start new task or enable auto-compact | 
| Slower responses | Model struggling with context | Reduce included files | 
| Repetitive suggestions | Context fragmentation | Summarize and start fresh | 
| Missing recent changes | Context overflow | Use checkpoints to track changes | 
 
Best Practices by Project Size
Small Projects (< 50 files)
- Any model works well
 
- Include relevant files freely
 
- No special optimization needed
 
Medium Projects (50-500 files)
- Use 128K+ context models
 
- Include only working set of files
 
- Clear context between features
 
Large Projects (500+ files)
- Use 200K+ context models
 
- Focus on specific modules
 
- Use search instead of reading many files
 
- Break work into smaller tasks
 
Advanced Context Management
Plan/Act Mode Optimization
Leverage Plan/Act mode for better context usage:
- Plan Mode: Use smaller context for discussion
 
- Act Mode: Include necessary files for implementation
 
Configuration:
Plan Mode: DeepSeek V3 (128K) - Lower cost planning
Act Mode: Claude Sonnet (1M) - Maximum context for coding
 
Context Pruning Strategies
- Temporal Pruning: Remove old conversation parts
 
- Semantic Pruning: Keep only relevant code sections
 
- Hierarchical Pruning: Maintain high-level structure, prune details
 
Token Counting Tips
Rough Estimates
- 1 token ≈ 0.75 words
 
- 1 token ≈ 4 characters
 
- 100 lines of code ≈ 500-1000 tokens
 
File Size Guidelines
| File Type | Tokens per KB | 
|---|
| Code | ~250-400 | 
| JSON | ~300-500 | 
| Markdown | ~200-300 | 
| Plain text | ~200-250 | 
 
Context Window FAQ
Q: Why do responses get worse with very long conversations?
A: Models can lose focus with too much context. The “effective window” is typically 50-70% of the advertised limit.
Q: Should I use the largest context window available?
A: Not always. Larger contexts increase cost and can reduce response quality. Match the context to your task size.
Q: How can I tell how much context I’m using?
A: CodinIT shows token usage in the interface. Watch for the context meter approaching limits.
Q: What happens when I exceed the context limit?
A: CodinIT will either:
- Automatically compact the conversation (if enabled)
 
- Show an error and suggest starting a new task
 
- Truncate older messages (with warning)
 
Recommendations by Use Case
| Use Case | Recommended Context | Model Suggestion | 
|---|
| Quick fixes | 32K-128K | DeepSeek V3 | 
| Feature development | 128K-200K | Qwen3 Coder | 
| Large refactoring | 400K+ | Claude Sonnet 4.5 | 
| Code review | 200K-400K | GPT-5 | 
| Documentation | 128K | Any budget model |