Compare LLM API prices and find the best-value AI model

By per-million-token pricing, open-source models like DeepSeek, plus Gemini Flash Lite and GLM, are usually the cheapest — output prices can be 10× lower than flagship models. The best choice depends on your quality bar, so sort the table above by price and cross-check the value score.

GPT-5.5 scores higher on multimodal and overall reasoning, ideal for flagship tasks mixing text, image and audio. Claude Sonnet 5 excels at coding and long-task reliability at a friendlier price. Favor Claude for code-heavy work and GPT-5.5 for an all-round flagship, then compare quality and cost on your actual tasks.

LLM APIs bill separately per million tokens for input (what you send) and output (what the model generates), with output usually several times more expensive. Monthly cost ≈ (avg input tokens × rate + avg output tokens × rate) × monthly requests. Use our cost calculator to estimate it directly.

RAG depends on both context window size and input token price, since retrieved documents consume a lot of input. Gemini's huge context plus low input pricing suits RAG well; for smaller corpora, a cheaper mid-tier model with good retrieval and caching keeps costs down.

Define your quality bar first, then compare input/output pricing, latency and speed, context length and modalities. Start from a scenario (coding, RAG, production), narrow down with the comparison table and recommendation wizard, and validate your monthly budget with the cost calculator.