Context Window
A context window is the maximum amount of text an AI model can process and 'remember' at once, measured in tokens. Larger context windows allow AI to understand more of your codebase, maintain longer conversations, and provide more relevant suggestions based on complete project context.
Example
With a 200K token context window, Claude can analyze your entire codebase at once. With only 4K tokens, the AI might forget what you discussed earlier in the conversation or miss relevant code in other files.
Context window is one of the most important concepts for effective vibe coding. It determines how much information AI can consider when generating responses — and directly impacts the quality of suggestions.
Why Context Window Matters
A larger context window means AI can:
- See more of your codebase simultaneously
- Remember earlier parts of your conversation
- Understand relationships between files
- Provide more consistent suggestions
Context Window Sizes (2025-2026)
| Model | Context Window |
|---|---|
| Claude 3.5 | 200K tokens |
| GPT-4 | 128K tokens |
| Gemini 1.5 | 1M+ tokens |
| Older models | 4K-8K tokens |
Practical Implications
Small context (4K-8K tokens):
- Good for single-file edits
- Loses track in long conversations
- Requires frequent context reminders
Large context (100K+ tokens):
- Can analyze entire applications
- Maintains coherent long sessions
- Understands cross-file dependencies
Working Within Limits
Even with large context windows:
- Focus on relevant code, not everything
- Summarize previous decisions when starting new sessions
- Use tools that intelligently select context (like Cursor)
- Be explicit about which files matter for current task
Cursor
Emergent — An agentic vibe-coding platform that builds production-ready apps