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12 QuestionsFind answers to common questions about AI API pricing, token costs, and how to use our calculator effectively. Can't find what you're looking for? Contact us.
A token is the basic unit of text that AI models process. Roughly, 1,000 tokens equals about 750 words in English. Tokens can be words, parts of words, or punctuation. Both input (your prompt) and output (the model's response) are counted and billed separately. Understanding tokens is essential for estimating your API costs accurately.
AI API cost is calculated based on the number of tokens processed. The formula is: Cost = (Input Tokens × Input Price per 1M / 1,000,000) + (Output Tokens × Output Price per 1M / 1,000,000). The calculator applies this formula to each verified pricing row.
AI model pricing varies based on model size, context window, provider infrastructure, cache policy, service tier, and market positioning. Some providers publish separate cache-hit, cache-miss, standard, priority, or long-context prices, so each row includes notes when a simple input/output price needs context.
Among the currently verified rows, DeepSeek V4 Flash has the lowest listed cache-miss input and output price. Kimi and MiniMax pricing depends more heavily on cache and service-tier assumptions. Always compare your expected input/output mix before choosing a model.
A context window is the maximum amount of text (in tokens) an AI model can process in a single request. Larger context windows can help with long documents or extended conversations, but using more context increases costs, so choose a model with an appropriate context window for your workload.
Key strategies include: 1) Use smaller/cheaper models for simple tasks, 2) Optimize prompts to be concise, 3) Implement caching for repeated queries, 4) Use model routing to send complex tasks to premium models only when needed, 5) Set max_tokens limits on outputs, 6) Monitor usage with observability tools. Our cost calculator helps you compare models and estimate savings.
The main pricing table only includes rows that have readable official source links. Each page shows the 'Price Data Last Verified' date and official source URL. Providers may still change prices without notice, so verify the linked official page before making business decisions.
Input tokens are the text you send to the model (your prompt, context, instructions). Output tokens are the text the model generates in response. Output tokens typically cost 2-5x more than input tokens because generating text requires more computation than processing it. This is why prompt engineering and limiting output length can significantly reduce costs.
Not always. The cheapest row can be best for high-volume simple tasks, but a more expensive model may reduce retries, shorten prompts, or produce better first-pass results. Treat price as one input, then test quality, latency, and failure rate.
As a rough guide: 1,000 tokens ≈ 750 words ≈ 1-2 pages of text. For code, 1,000 tokens ≈ 50-100 lines depending on language. Use our Token Estimation Guide in the calculator to see common scenarios. For precise estimation, use the tokenizer or token-counting endpoint provided by your selected model vendor.
DeepSeek is an AI provider whose official pricing page currently lists very low V4 Flash and V4 Pro token prices, with separate cache-hit and cache-miss input rates. The calculator uses cache-miss input prices as the conservative default. Consider data residency, compliance, latency, and product requirements before choosing any provider.
Yes. Many production applications use routing to send simple tasks to cheaper models and harder tasks to stronger or faster tiers. Our comparison tools help estimate the cost side of that decision, while your own tests should decide quality and reliability.