What is Token Limit?
Last updated May 2026The maximum number of tokens that can be processed in a single API request.
Definition
Token limits define the maximum input and output sizes for AI API calls. Each model has specific limits: GPT-4o supports 128K input tokens, Claude supports 200K. The limit includes both your prompt and the AI response. Exceeding the limit requires chunking strategies, summarization, or using models with larger context windows.
💡 Example
If you try to paste a 300-page PDF into ChatGPT, you will hit the token limit. Solutions include using Claude (200K tokens = ~150K words), splitting the document into sections, or using RAG to retrieve only relevant passages.
Related concepts
A type of AI trained on massive text datasets to understand and generate human language.
The basic unit of text that AI models process — roughly 4 characters or 0.75 words.
The maximum amount of text an AI model can process in a single conversation.
Why this matters
Token limits cap how much text an AI can process in one request. Hitting token limits truncates your input or forces you to split tasks. Understanding limits helps you choose the right model for your document length and optimize prompts for efficiency.
Real-world example
If you paste a 200-page document into ChatGPT Free (8K token limit), it can only see the first ~12 pages. With ChatGPT Plus (128K tokens), it sees ~190 pages. With Claude (200K tokens), it sees the entire document. For long documents, token limits drive tool choice.
See it in action
A way for developers to programmatically access AI models in their own applications.
What is Token Limit?
Token limits define the maximum input and output sizes for AI API calls. Each model has specific limits: GPT-4o supports 128K input tokens, Claude supports 200K. The limit includes both your prompt and the AI response. Exceeding the limit requires chunking strategies, summarization, or using models with larger context windows.
How does Token Limit work in practice?
If you try to paste a 300-page PDF into ChatGPT, you will hit the token limit. Solutions include using Claude (200K tokens = ~150K words), splitting the document into sections, or using RAG to retrieve only relevant passages.
What is the difference between context window and token limit?
Context window refers to the total number of tokens a model can process in a single interaction (input plus output). Token limit can refer to either the context window or a maximum output length cap. Some APIs let you set a max output token limit separately from the model's overall context window.
How can you work within token limits effectively?
Strategies include summarizing long documents before sending them, breaking large tasks into smaller chunks, being concise in system prompts, removing unnecessary context from conversations, and using models with larger context windows for document-heavy tasks.
What happens when you hit a token limit?
When you reach the input token limit, the API returns an error or the interface truncates older messages. When you hit the output token limit, the model's response cuts off mid-sentence. Planning for these limits by structuring requests appropriately helps avoid incomplete or failed responses.