Context Window Calculator

A good rule of thumb is ~0.75 words per token, or about 4 characters per token, for typical English text. So 50,000 words is roughly 67,000 tokens, and a 500-word page is about 670 tokens. Code, other languages, and unusual formatting tokenize differently, so treat the estimate as a ballpark, not an exact count.

By verified API context windows, GPT-5.5 leads at ~1.05M tokens, with Gemini 3.1 Pro, Claude Opus 4.8 / Claude Sonnet 4.6, Grok 4.3, and the open Llama 4 Maverick all at ~1M. Google has discussed a larger Gemini tier (~2M) and Meta a 10M Llama 4 Scout variant, but those aren't standard API rows. For very long inputs, watch for context-tiered pricing: several models charge more above ~200K tokens.

Two ways. First, processing more tokens costs more directly (price × token count), which this tool shows as the per-run input cost. Second, several flagships charge a higher per-token rate once a prompt passes ~200K tokens, so a 500K-token prompt can cost more than 2.5× a 200K one. Always leave headroom for the model's reply, too.

If your text fits comfortably and you query it once or twice, a long context is simplest. If you have a large, mostly-static corpus you query repeatedly, retrieval (RAG) is usually cheaper and faster; you only send the relevant chunks each time instead of paying for the whole document on every call.