Know what your AI feature will cost before you ship it.
Compare checked provider pricing, estimate workload spend, and monitor price changes from one clean decision surface.
Tracking 38 models across 6 providers in the current dataset.
Sample workload
Customer support automation
GPT-5.4 mini · OpenAI
Estimated monthly spend
$3,480
Cost per request
$0.002
Annual run rate
$41,764
The Platform
One place to compare prices, model spend, and track changes
01
Model pricing directory
See checked input, output, cached-input, and batch pricing across major providers in one normalized view.
02
Workload cost calculator
Turn token pricing into per-request, monthly, and annual spend using the inputs your team actually plans around.
03
Pricing change log
Catch launches and price moves early so you can recheck margin before the bill changes.
Pricing Snapshot
Checked model pricing from the current dataset
| Model | Provider | Input / 1M | Output / 1M | Checked |
|---|---|---|---|---|
| GPT-5.4 mini | OpenAI | $0.75 | $4.50 | 2026-04-24 |
| Claude Sonnet 4.6 | Anthropic | $3.00 | $15.00 | 2026-04-24 |
| Gemini 2.5 Pro | Google Gemini | $1.25 | $10.00 | 2026-04-24 |
| DeepSeek Chat | DeepSeek | $0.28 | $0.42 | 2026-04-24 |
Simulation
Start from a real workload, not a blank spreadsheet
Use workload presets to model support bots, RAG assistants, and coding agents with the inputs teams actually plan around.
Open cost calculatorRAG chatbot
Estimate spend for retrieval-heavy assistants that repeatedly pull large context windows.
Customer support bot
Estimate support automation volume and see how quickly a high-usage inbox can move margin.
Coding agent
Estimate output-heavy coding assistant usage where long generations can dominate cost.
Support
Questions teams ask before they lock in a model
Get to a usable cost number before launch
Compare models, test a workload, and keep provider pricing visible before it changes product margin.
Need saved estimates or manual price alerts?
Email us for saved estimates, manual alert requests, or pricing corrections before you commit to a model.