Inference Cost
The computational expense of running a trained AI model to generate outputs. Measured in cost per token or per request. Varies dramatically between models — GPT-4 class models cost 10-50x more per token than smaller models.
Why it matters
Training a model is a one-time expense, but inference, the cost of actually running it to answer prompts, is paid every single time someone uses it. For any real product, this is the bill that grows with popularity. It's why teams care so much about model size, caching, and routing, and why the price gap between a small model and a top-tier one can be enormous for the same task.
In practice
A startup launches a chatbot and it goes viral. Each message runs the model, and those cents per request pile up into thousands of dollars a day. To keep the doors open, they route easy questions to a cheaper model and reserve the expensive one for hard cases. Comparing per-token prices across options on an aggregator like Vincony helps them pick the most cost-effective model for each job.
Related terms
Agentic AI
AI systems that operate autonomously over extended tasks — planning, executing, and self-correcting without step-by-step human guidance. Unlike chatbots, agentic AI sets sub-goals, uses tools, and adapts its strategy based on intermediate results.
AI Agent
An autonomous AI system that can perceive its environment, make decisions, and take actions to achieve goals — like managing your email, scheduling meetings, or monitoring data.
ATS (Applicant Tracking System)
Software used by employers to filter and rank job applications by scanning resumes for keywords, formatting, and relevance. AI resume builders optimize output to pass ATS screening.
Benchmark
A standardized test or dataset used to evaluate and compare AI model performance. Common benchmarks include MMLU (knowledge), HumanEval (coding), and MT-Bench (conversation). Helps users choose the right model for their needs.
Brand Kit
A centralized collection of brand identity elements — logos, color palettes, typography, voice guidelines, and visual style rules — used to ensure consistent AI-generated content matches your brand.
BYOK (Bring Your Own Key)
A model where users provide their own API keys for AI services (like OpenAI or Anthropic) instead of using the platform's shared access. Offers more control over usage, billing, and rate limits.