AI & LLM
Token, cost & context tools for LLMs
Does My Prompt Fit? — LLM Context Window Checker
Before sending a large prompt to an LLM API, check whether it fits within the model's context window. The usable input space is not the same as the context window: you must reserve tokens for the model's response. For GPT-5.5, with 32,000 tokens reserved for output, the usable input is 1,018,000 tokens (context window 1,050,000 − reserved 32,000). An 800,000-token prompt fits comfortably. Paste your prompt and select a model to check fit instantly — no API call needed.
Model: GPT-5.5 | Context window: 1,050,000 tokens
- Reserved for output: 32,000 tokens
- Usable input space: 1,018,000 tokens
- Example prompt (800,000 tokens): FITS ✓
- Over-by: 0 tokens (none — fits)
- Data as of 2026-07-03
Frequently asked questions
How do I check if my prompt fits in the context window?
1. Count your prompt tokens (paste text into the Token Counter — linked in the tools cluster). 2. Subtract the tokens you need to reserve for the model's response (e.g. 1,000–32,000 depending on response length). 3. If your prompt token count is less than context window − reserved output, it fits. For GPT-5.5: 1,050,000 − 32,000 = 1,018,000 usable input tokens. This checker does steps 2–3 automatically.
What happens if my prompt exceeds the context window?
If your combined input + output tokens exceed the model's context window, the API returns an error (e.g. "maximum context length exceeded"). The model does not silently truncate your input — the call fails. Solutions: shorten the prompt (remove less-relevant context), use chunking (process documents in sections), switch to a model with a larger context window, or use retrieval-augmented generation to include only the most relevant document sections.