Step-by-step reasoning instructions often increase output length. Use concise justification unless detailed reasoning is required.
AI Prompt Cost Optimizer
Reduce prompt length, compare token usage, and estimate how much your AI API cost can drop before you ship.
Runs locally
Compare prompt cost before and after optimization
Local rule engine
Generated optimized draft
This draft is created in your browser without any AI API call. It updates automatically as you edit, removes repeated sentences, replaces high-cost wording, limits output length when useful, and compresses oversized context into a practical instruction.
The prompt asks for many formats, examples, caveats, or explanations. The local draft keeps only useful next steps or required format.
The local engine merged overlapping concise-answer instructions into a cleaner optimized prompt.
Local estimate only. Provider tokenizers, cached-input billing, batch discounts, retries, and official invoices may differ.
How to reduce prompt cost without hurting quality
The goal is not to make every prompt tiny. The goal is to remove repeated instructions, unnecessary context, and uncontrolled output length while keeping the information the model needs to complete the task.
Remove repeated instructions
Keep durable behavior in the system prompt and avoid repeating style, tone, and safety instructions in every user prompt.
Limit retrieved context
Send only the most relevant passages instead of whole documents, long chat history, or duplicated knowledge base snippets.
Control output length
Use task-aware output control: JSON-only for extraction, final code for coding tasks, concise recommendations for decisions, and focused structure for long-form content.
Route simple work to cheaper models
Use small or lite models for classification, extraction, rewriting, formatting, and other predictable prompt paths.
Why prompt optimization matters
Small prompt changes can become meaningful cost savings when a workflow runs thousands of times per day. Repeated instructions, oversized retrieved context, long examples, and unconstrained responses all increase token usage before a user sees any value.
What this optimizer calculates
The tool compares an original prompt with an optimized version, estimates token reduction, applies the selected model's input-token price, and forecasts savings per run, per day, per month, and per year.
How teams should use it
Use this page before changing production prompts. Test whether a shorter prompt preserves the key instruction, required context, output format, and quality bar. For high-risk workflows, validate changes with real examples before shipping.
Example: repeated instruction cost
If the same 250-token style guide is repeated in 100,000 monthly requests, that style block alone becomes 25 million input tokens. Moving durable behavior into a system prompt, shortening repeated wording, or caching stable context can reduce cost without changing the user experience.
Local engine now, official API later
The current free optimizer runs locally and uses rules for repeated sentences, high-cost phrasing, long context, missing output limits, and verbose English wording. A paid API-powered optimizer is reserved for Pro and Team plans so members can later receive more precise model-assisted prompt rewrites.
Global support roadmap
More language-specific prompt optimization rules are coming soon.
Formula for savings
Estimated monthly savings = saved input tokens per run / 1,000,000 x model input price x runs per day x 30. The estimate focuses on input-token savings; output-token changes should still be tested with real examples.
Prompt optimization disclaimer
Disclaimer: All prices, token counts, forecasts, comparisons, and cost calculations are estimates for general planning only. They are not financial, tax, accounting, procurement, purchasing, or legal advice. AI providers may change pricing, billing units, model names, discounts, and terms at any time. Always verify current pricing on the provider's official pricing page. The official provider bill, billing dashboard, and invoice are the final source of truth.
Turn prompt savings into a full API budget.
Use the API Cost Calculator to include output tokens, request volume, and user-scale forecasts.
FAQ
What is an AI prompt cost optimizer?
An AI prompt cost optimizer compares prompt versions, estimates token reduction, and forecasts how much API input cost may drop when a shorter prompt is used at production volume.
Does this tool rewrite my prompt with an AI model?
No. This first version runs locally and does not call OpenAI, Claude, Gemini, DeepSeek, Grok, or any other AI provider. You paste both versions and compare the cost impact.
Can shorter prompts reduce quality?
Yes. Removing useful context, constraints, or examples can reduce answer quality. The safest approach is to remove repetition and irrelevant context first, then test optimized prompts against real examples.
Why does output length matter for prompt cost?
Output tokens are often more expensive than input tokens. A good prompt can reduce cost by controlling both the prompt length and the model's expected response length.
Are the savings exact?
No. Savings are planning estimates only. Provider tokenizers, cached-input billing, batch discounts, retries, and official invoices can differ.