Every developer building on AI APIs hits the same wall eventually.
You pick a model, start building, and then suddenly you're staring at your billing dashboard wondering where all your credits went. GPT-4o for everything sounds great until you're running 10,000 prompts a day and the invoice arrives.
I built AI API Cost Calculator to solve this exact problem — for myself first, and then for everyone else.
The problem with comparing AI pricing
Every provider publishes their pricing on their own page, in their own format, with their own terminology. OpenAI talks about input and output tokens separately. Anthropic prices per million tokens. Google has free tiers that complicate the math. And none of them tell you what your actual prompt will cost before you send it.
So every time a new model drops, developers are stuck doing mental math across five browser tabs.
What the tool does
It's a single page. You paste your prompt. It instantly shows you:
Token count, word count, character count
Exact cost across GPT-4o, GPT-4o mini, Claude Sonnet, Claude Haiku, Gemini 1.5 Pro, Gemini Flash, and Llama 3.1 via Groq
Which model is cheapest for that specific prompt
A batch estimator — if you run this prompt 10,000 times a day, here's your monthly bill
No signup. No account. No data sent anywhere. Everything runs in your browser.
What surprised me about the pricing differences
Once I had all the numbers in one place, the gaps were bigger than I expected.
Running the same prompt 10,000 times a day costs roughly $45/month on GPT-4o. The same workload on Gemini Flash costs under $2. That is not a rounding error. That is a 95% cost reduction for use cases where response quality is similar enough.
For most classification tasks, summarisation, and structured output generation — Gemini Flash and Claude Haiku are genuinely good enough. The expensive models earn their price on reasoning-heavy tasks, long context, and nuanced generation. But most production pipelines are not doing that for every single call.
The batch estimator makes this very concrete. Slide it to your actual daily volume and watch the monthly cost column. That number tends to focus the mind.
Why I built it in a weekend
The tool is a Next.js app deployed on Vercel. No backend. All pricing lives in a single TypeScript constants file that takes about five minutes to update when providers change their rates. The token count is an estimate based on the standard 1 token ≈ 4 characters heuristic, which is accurate enough for budgeting purposes.
I wanted something I could actually use in my own workflow before committing to a model for a new feature. Now I just open the tab, paste the system prompt, and the answer is immediate.
Go try it
If you're building anything on AI APIs — whether it's a side project, a production system, or just experimenting — bookmark this.
👉 AI API Cost Calculator
It's free, it's fast, and it might save you from a billing surprise at the end of the month.
If you find it useful, share it with someone else who's building on AI. And if the pricing data ever looks wrong, the update takes five minutes — just drop a comment and I'll fix it.
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