Context Windows: How Much AI Can 'Remember'

Each AI can only 'remember' a certain amount of text in one chat. This is the context window. Bigger window = can handle longer documents. Understanding this saves you from confusion.

Some examples

• GPT-4 / Claude: huge context windows now (millions of tokens).
• Smaller models: smaller windows.
• If your chat gets very long, AI may forget early stuff.
• For long documents, paste the whole thing at the START of the chat.

Try it!

Understanding "Context Windows: How Much AI Can 'Remember'" in practice: Understanding AI in this area gives you a real advantage in how you work and think. Each AI has a 'context window' — how much it can hold in memory. Knowing this matters for big tasks — and knowing how to apply this gives you a concrete advantage.

• Apply context window in your model-families workflow to get better results
• Apply AI memory in your model-families workflow to get better results
• Apply limits in your model-families workflow to get better results

1. 1Apply Context Windows: How Much AI Can 'Remember' in a live project this week
2. 2Write a short summary of what you'd do differently after learning this
3. 3Share one insight with a colleague

Context window = how much text you can paste in one go. Claude offers 200K (or 1M for some). GPT-5 offers 400K. Gemini offers 2M (about a Lord of the Rings book). Sounds amazing — but research shows models get worse at finding info in the middle of long contexts ('lost in the middle'). More context isn't always better quality.

Some examples

• Pasting a 500-page PDF and asking 'what does it say?' — surface info works fine.
• Asking 'find the one sentence about taxes on page 213' — performance drops noticeably.
• For long docs, splitting into chunks and asking targeted questions often beats one big paste.
• RAG (retrieval-augmented generation) tools like NotebookLM are designed exactly for this.

Try it!

Take a long article (10+ pages). Paste into Gemini and ask a specific question. Then split it into 3 parts and ask the same question. Compare answers.

The context window is how much text the model can read at once. GPT-3 had 4,000 tokens (a few pages). Claude 4.5 has 200k+ (a small book). Gemini 2.5 has 1-2 million (a whole textbook). Bigger context = more material the AI can reason over without needing summaries.

Some examples

• You drop a 300-page novel into Gemini and ask 'what foreshadowing did chapter 3 contain about chapter 27?'
• You paste a whole codebase into Claude and ask 'where would I add a feature flag?'
• You paste 30 PDFs of research into Gemini and ask for a meta-analysis.
• You paste a 2-hour transcript of a podcast and ask for chapter timestamps.

Try it!

Find a long document (a novel, a codebase, a course textbook). Paste as much as you can into Gemini or Claude. Ask a question that requires connecting two distant parts.