Comparing Token Costs: What Does AI Actually Cost to Use?
A practical breakdown of what tokens mean in real terms — from a single email to processing an entire codebase.
GPTUni Team
One of the most common questions from developers and businesses evaluating AI models is: "What will this actually cost me?" Token-based pricing can be confusing if you are not familiar with how language models process text. This guide breaks it down in practical terms.
A token is roughly 3/4 of a word in English. A 1,000-word article is approximately 1,333 tokens. A 10-page report is about 7,500 tokens. A full-length novel is around 100,000-150,000 tokens.
Here is what common tasks cost across different pricing tiers:
Summarizing a 1,000-word article (1,333 input tokens, ~200 output tokens): - Budget model (Gemini Flash): $0.0001 — essentially free - Mid-tier (GPT-4.1 mini): $0.0005 - Frontier (Claude Opus 4): $0.035
Processing a 50-page legal contract (37,500 tokens input, 2,000 tokens output): - Budget: $0.004 - Mid-tier: $0.02 - Frontier: $0.71
Analyzing a 10,000-line codebase (50,000 tokens input, 5,000 tokens output): - Budget: $0.007 - Mid-tier: $0.03 - Frontier: $0.95
Running a customer support chatbot (1,000 conversations/day, avg 2,000 tokens each): - Budget: $0.20/day, $6/month - Mid-tier: $1/day, $30/month - Frontier: $45/day, $1,350/month
The takeaway: for most applications, AI model costs are very manageable at the mid-tier level. Frontier models make sense for high-value tasks where quality is critical, while budget models work well for high-volume, lower-complexity tasks. Many production systems use a combination, routing simple requests to cheaper models and escalating complex ones to frontier models.