Best Free AI Tools for Small Business in 2026 (No Sign-Up Required)
Looking for the best free AI tools for small business in 2026? Skip the sign-ups and subscriptions. Here's a lean toolkit for…
Free Tool
LLM Token Cost Calculator
How much do GPT, Claude, and other LLMs cost per token? Enter your usage to see cost per request, per month, and per year — and compare every model side by side.
Instant calculation
Runs in your browser
Compare all models
Cost per request
$0
Representative list prices (updated —) — providers change rates often, so verify on the official pricing page. Token counts vary by content.
Building with AI? We'll architect it cost-efficiently — book a free consultation →
No spam — we only use this to send your breakdown and follow up about your project.
The same usage, priced across every model
Cheapest to most premium — at your current input/output/volume.
LLM Token Cost Calculator: Turn Per-Token Pricing Into a Monthly Bill
Why Use This LLM Token Cost Calculator?
AI pricing looks cheap per token and stops looking cheap around the second month. The Parix.ai LLM token cost calculator turns a per-million-token price into a monthly figure you can actually put in a budget.
The reason estimates go wrong is that almost nobody gets volume right on the first attempt. A workflow that felt small in testing runs ten thousand times in production, and the bill arrives without warning.
The Thing Most People Get Wrong
Output tokens cost roughly five times what input tokens cost on every major model.
That single fact changes which model makes sense. A task that reads a long document and writes a short summary is cheap on any tier. A task that generates long reports is where the tier choice hits hardest — and it is the one people assume will be similar.
Estimate input and output separately. Treating them as one number produces an answer that is wrong by a factor of several.
How to Estimate Your Volume
Count the runs. How many times a day does this workflow fire?
Estimate tokens per run. Roughly 750 words per 1,000 tokens — the Token Counter gives you an exact figure for a real sample.
Split input and output. They price differently.
Add a margin. Retries, failed runs and testing all consume tokens that nobody budgets for.
Two Discounts That Change the Answer
Batch processing is typically 50% off both input and output. If the work is not time-sensitive, this halves the bill for no engineering effort.
Prompt caching charges roughly 10% of the base input price for cached reads. If your workload repeats the same long system prompt on every call — and most production workloads do — caching alone can change which model is affordable.
The Number That Actually Matters
Not price per token. Cost per completed task.
A cheaper model that fails one time in three is more expensive than a pricier one that finishes, once you count the retries and the human cleanup. Run both on the same job, with the same prompt and the same definition of done, then compare totals. The AI Model Comparison Table lists the per-model pricing to start from.
This is also why picking the cheapest model is as naive as always picking the best one. Neither is a strategy.
Who Uses It
Engineering leads sizing a feature before it ships. Founders working out whether an AI product has a margin. Finance teams handed an API invoice they were not expecting. Pair it with the API Cost Calculator for the non-AI services in the same workflow, and our AI integration team if you want the estimate checked against a real build.
Estimate Your Bill Now
Enter your volumes above and see the monthly figure before the invoice does.
