LLM token costs scale with three variables: requests per day, average context length (input tokens), and the model's per-token pricing. GPT-4o charges $2.50/M input tokens and $10/M output tokens. Claude Sonnet charges $3.00/$15.00. Llama 3.1 70B hosted charges $0.59/$0.79 - 5x cheaper for high-volume workloads. Semantic caching stores embeddings of previous inputs and returns cached responses for semantically similar queries, reducing effective input token cost by 30-40% on repetitive workloads like RAG.
Compare GPT-4o, Claude Sonnet, and Llama 3.1 70B hosted on identical workloads - see the cost difference at 50K requests/day
Adjust context length from 512 to 8K tokens - output cost grows proportionally, input cost grows with context
Toggle semantic caching to see 35% savings on input tokens for repetitive queries like RAG lookups
Track the monthly cost alert threshold - get a visual warning when projected spend exceeds $5,000/month
Part of the EngineersOfAI Interactive 3D - free interactive visualizations covering every major concept in machine learning and AI engineering. Hover any element for a plain-English explanation. No code required.