Direct Answer GPT-4’s maximum token limit depends on the specific model variant and how it’s used. For most developers, the standard GPT-4 model supports a context window of up to 128,000 tokens, which includes both the input (prompt) and output (response). This means the combined tokens from the user’s input and the generated text cannot exceed 128,000 tokens in a single interaction. For example, if a prompt uses 100,000 tokens, the response can only generate up to 28,000 tokens. Earlier GPT-4 variants, like the 8k or 32k versions, have lower limits, but the 128k model is now the default for most API and enterprise use cases.
Tokenization and Practical Examples Tokens are chunks of text processed by the model, roughly equivalent to 4 characters or 0.75 words in English. The 128k token limit allows handling large inputs, such as lengthy documents or codebases. For instance, a 300-page book (approximately 150,000 words) would require about 200,000 tokens, exceeding GPT-4’s limit. Developers working with such content must split it into segments. Conversely, a 50-page technical specification (around 30,000 words) fits comfortably within the 128k limit, leaving room for detailed responses. Tools like OpenAI’s tokenizer help count tokens accurately, ensuring prompts stay within bounds.
Developer Considerations
When integrating GPT-4, developers must manage token limits programmatically. For example, if building a chatbot, truncating or summarizing prior conversation history prevents exceeding the context window. API parameters like max_tokens cap the response length, but input and output combined must stay under 128k. Exceeding this causes errors, so input validation is critical. For tasks like analyzing code repositories, splitting files into smaller chunks or using embeddings to reduce context size are common strategies. While the 128k limit is substantial, balancing input complexity and output needs remains key to avoiding rate limits or performance trade-offs.