The Memory Limit

Every AI model has a context window. It's the maximum amount of text the model can consider at one time. Think of it as the model's working memory.

When your conversation exceeds the context window, the model starts "forgetting" earlier parts of the conversation. It's not a bug. It's a fundamental limitation of how these models work.

Context Windows by Model

Context windows vary dramatically:

• GPT-4o: 128K tokens (roughly 96,000 words)
• Claude: Up to 200K tokens (roughly 150,000 words)
• Gemini Pro: 1M+ tokens (roughly 750,000 words)
• Llama models: Varies, typically 8K-128K tokens

One token is roughly 3/4 of a word, so 100K tokens is about 75,000 words.

Why It Matters

Long conversations

If you're 50 messages into a conversation, a model with a small context window might not remember what you discussed at the beginning.

Document analysis

Want to analyze a 100-page document? You need a model with a large enough context window to hold the entire document plus your conversation about it.

Code review

Reviewing an entire codebase requires fitting all the files into the context window at once for the model to understand relationships between components.

Signs You've Exceeded the Context Window

• The model contradicts something it said earlier
• It forgets instructions you gave at the start
• It asks for information you already provided
• Responses become less relevant to the overall conversation

How to Work Around It

Start new conversations

For new topics, start a fresh chat instead of continuing a long thread.

Front-load important context

Put your most important instructions and information at the beginning of the conversation.

Summarize periodically

Ask the model to summarize the conversation so far, then start a new chat with that summary as context.

Choose the right model

For tasks involving long documents or extended conversations, choose a model with a larger context window. Claude's 200K token window can handle entire books.

How Octofy Helps

Octofy shows a context overflow indicator when your conversation approaches the model's limit. Automatic model selection also considers context length when choosing a model, routing longer conversations to models with larger windows.