Check Context Window Utilization for GPT-4o

GPT-4o supports a 128,000-token context window — enough for roughly 100,000 words or about 90% of a typical novel. But context windows are not free to use: every token in the context is processed on every forward pass, and input token costs apply to the full context regardless of how old those tokens are. Understanding your utilization prevents unexpected truncation errors and helps you design conversation management strategies before they become production problems. This example models a realistic GPT-4o deployment with a detailed system prompt, a 15-turn conversation history, and a long user-provided document for analysis. The calculator shows utilization as a percentage of the 128K limit and indicates how many tokens remain for the model's response. When remaining capacity is less than your typical response length, the API truncates the response silently — a bug that is often misattributed to model quality rather than context management. For the GPT-4o-mini model, the context window is also 128K but the input token pricing is about 8x cheaper, making it feasible to maintain much longer conversation histories without significant cost impact. The o1 and o3 models have different context windows and should be checked separately.

Model: gpt-4o
Context window: 128000 tokens

System prompt (tokens): 680
Conversation history (15 turns, ~120 tokens each): 1800
Attached document for analysis (tokens): 4200
Latest user message (tokens): 95

Reserved for response: 2000