In 2026, a single API call for large language models can cost from a fraction of a cent to over a dollar, with the gap between the cheapest and most expensive flagship models exceeding 100x. The guide compares API pricing across providers including OpenAI, Anthropic, Google, DeepSeek, Kimi, MiMo, and MiniMax, covering prompt caching mechanics, tokens-per-second, and hidden costs. The article includes a master pricing table and sections on OpenAI’s GPT-5.6 family, Anthropic’s Claude models (Opus 4.8, Fable 5, Sonnet 5, Haiku 4.5), Google Gemini (Pro, Flash, Flash-Lite), and Chinese AI APIs from DeepSeek, Kimi, MiMo, and MiniMax. It also addresses mid-tier contenders like Grok, Muse, GLM, Qwen, and Nemotron, as well as OpenRouter and third-party inference providers. Topics include automatic vs. manual caching, cache hit rate variability, and hidden costs such as reasoning tokens, tokenizer differences, cache write costs, rate limits, cold starts, and multi-modal input costs. The guide provides examples for estimating monthly spend, including a customer support chatbot, high-volume document classification, and a coding assistant with reasoning.