AI tooling

GPT vs Claude vs Gemini: what tokens actually cost

Model list prices change often. Estimate a real prompt in your browser — no API key, no paste into a third-party calculator that stores text.

LLM Cost Estimator Token Counter

Unit economics

Why token counts matter

LLM APIs bill by tokens, not characters. A “10K-token prompt” can cost very different amounts by model tier, input vs output rates, and cached context.

Input ≠ output

Completion tokens are usually priced higher. Always model both sides of a request.

Volume multiplies

A few cents per call becomes a real monthly bill when a feature hits every user.

Keep prompts local

Count and cost-estimate in-browser before you paste production text into a vendor console.

Playbook

Quick comparison workflow

Count tokens

Paste system + user text into the Token Counter.

Estimate cost

Open the LLM Cost Estimator and pick models.

Set volume

Enter input/output counts or paste text; project monthly spend.

Scan PII

Run the Prompt PII Scanner — or use synthetic samples.

Sanity check

Example: 10K in, 2K out

Exact prices change — always verify against provider pages. The estimator uses published list prices so you can challenge vendor quotes and wrapper unit economics.

OpenAI GPT

Check current input/output rates and cached-input discounts on the official pricing page.

openai.com/api/pricing

Anthropic Claude

Compare Haiku / Sonnet / Opus tiers — output tokens usually dominate long generations.

anthropic.com/pricing

Google Gemini

Flash vs Pro (and context-window SKUs) shift the 10K-token story more than character count.

ai.google.dev/pricing

Repeatable

Chain it in Recipe Studio

Same pattern as Ship AI prompts safely — count, cost, then scan.

token-counter llm-cost-estimator prompt-pii-scanner

Open Recipe Studio