Context windows define how much text an LLM can process at once.
Learn to work within token limits for better results.
What is a Context Window?
The maximum number of tokens an LLM can process in a single request.
Context Window Sizes
GPT-3.5: 4K tokens
GPT-4: 8K-32K tokens
GPT-4 Turbo: 128K tokens
Claude 3: 200K tokens
DeepSeek: 64K tokens
Strategies for Long Documents
1. Chunking: Split into smaller pieces
2. Summarization: Reduce content size
3. RAG: Use retrieval-augmented generation
4. Sliding window: Process in sections
Code Example: Chunking
def chunk_text(text, max_tokens=4000):
words = text.split()
chunks = []
for i in range(0, len(words), max_tokens):
chunks.append(‘ ‘.join(words[i:i+max_tokens]))
return chunks
Best Practices
✅ Reserve tokens for system prompt
✅ Leave room for model response
✅ Use compression techniques
Conclusion
Understanding context windows is crucial for LLM applications!