> ## Documentation Index > Fetch the complete documentation index at: https://docs.rockapi.ai/llms.txt > Use this file to discover all available pages before exploring further. # Cheap AI API: how to lower LLM token costs without rewriting your app > Compare direct AI API pricing with gateway pricing and learn how Rock API helps teams reduce OpenAI, Anthropic, and Gemini model costs. # Cheap AI API: how to lower LLM token costs without rewriting your app The cheapest AI API is not always the model with the lowest sticker price. Real cost depends on input tokens, output tokens, cached tokens, retries, model choice, and whether your team pays platform fees on top of provider pricing. Rock API gives developers OpenAI-compatible access to supported premium models at **0.7x standard pricing**, which means a flat **30% savings** on supported upstream AI model usage. AI API cost comparison chart showing Rock API at 700 dollars for an example 1000 dollar monthly model spend ## Start with the monthly spend pattern Before you compare gateways, calculate your current spend by model and token type. | Cost driver | What to check | | ------------- | ----------------------------------------------------------------------- | | Input tokens | Long prompts, system messages, and retrieved context. | | Output tokens | Chat answers, agent traces, code generation, and summaries. | | Cached tokens | Repeated prefixes and reusable context where providers support caching. | | Retries | Failed requests and timeout recovery. | | Provider mix | Whether you use OpenAI, Anthropic, Google, or several providers. | If a team spends $1,000 per month on supported AI API calls, a 30% discount reduces the model bill to $700. At $10,000 per month, the same discount saves $3,000 per month or \$36,000 per year. ## Cheap AI API options compared | Option | Best for | Cost tradeoff | | -------------------- | ------------------------------------- | ------------------------------------------------------------------------------- | | Direct provider APIs | Simple single-provider projects | Standard provider pricing and separate billing. | | OpenRouter | Discovery across many models | Often standard or above-standard pricing depending on model and route. | | LiteLLM | Teams that want self-hosted routing | Software is open source, but you still pay provider pricing and infrastructure. | | Rock API | Teams using supported top-tier models | 0.7x pricing with one OpenAI-compatible interface. | ## How to reduce LLM API costs 1. Choose the smallest model that meets the task quality bar. 2. Track input and output tokens separately. 3. Use cached-token pricing when available. 4. Remove repeated prompt text that does not change outcomes. 5. Centralize usage so teams see spend before invoices arrive. 6. Compare direct provider pricing with gateway pricing. ## FAQ ### What is a cheap AI API for production apps? A production AI API should be low-cost, compatible with your client, observable enough for billing review, and stable enough for real traffic. A low per-token price is only useful if the integration does not add reliability or maintenance problems. ### How can I reduce OpenAI API cost? Start by measuring token usage, switching simple tasks to smaller models, using cached tokens where possible, and comparing direct provider pricing with discounted gateway pricing. Rock API can reduce supported model usage by 30% through 0.7x pricing. ### Is prepaid billing useful for AI APIs? Prepaid billing helps teams avoid surprise invoices. You add balance first, usage is deducted in real time, and the application stops when balance is exhausted instead of creating overage charges. ## Next step For a provider-by-provider model guide, read [AI model API comparison](/blog/buyers/ai-model-api-comparison).