Token
Also known as: AI token, LLM token.
In plain English
Tokens are created by a tokenizer that breaks text into subword units. Common English words ('the', 'and', 'is') are one token. Rare words and non-Latin scripts can be many tokens. Code is typically 0.5 tokens per character. Most LLM pricing is structured per million tokens for input and a higher per million for output (output is more expensive because it takes more compute to generate). Understanding tokens matters for cost control: shorter prompts and constrained outputs (e.g. 'reply in 100 words') directly reduce spend.
Example
The sentence 'The quick brown fox jumps over the lazy dog' is 9 words but 10 tokens in GPT's tokenizer. A 2,000-word blog post is roughly 2,700 tokens of output. At GPT-5.2 pricing ($10 per 1M output tokens), generating that blog post costs about $0.027.
Token in Vincony
Vincony uses a credit-based pricing model that abstracts token math — you see 'credits' per generation, not raw token counts. The Credits Calculator estimates what your typical usage will cost.
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