Every single time we design a new AI feature, our product managers ask the exact same question: "What is this going to cost us at scale?" It sounds like a simple request. But as any developer knows, calculating true LLM pricing is an absolute engineering nightmare. API prices change weekly, output tokens cost $3\times$ to $5\times$ more than input tokens, and multi-turn chat history scales quadratically ($O(N^2)$). Trying to map out complex workload shapes on a spreadsheet was breaking my brain. After the third time a PM asked me to run a "what-if" scenario comparing a premium frontier model against a cheaper open-weights alternative, I decided to stop messing with Excel formulas and build a dedicated solution. Say hello to ChooseAIModel (chooseaimodel.com) - a zero-auth, zero-code cost simulator built specifically to bridge the gap between engineering reality and business budgeting. 🚀 What it does: Simulate Real Workload Shapes: Paste a real prompt, mock file sizes (like a 2MB PDF or CSV), and set your expected monthly volume to get an instant token calculation. Trace Multi-Turn Conversation Math: Drop in follow-up chat turns to see exactly how your context grows, complete with automatic prompt caching discounts mapped out. Compare 290+ Models Side-by-Side: Instantly see your projected monthly bill compared across 49 different providers - from ultra-premium reasoning engines to highly efficient mid-tier models. It’s completely free, requires no SDK, no account, and stores absolutely zero data. If you are tired of guessing your cloud bills or manually tracking vendor rate sheets just to answer a roadmap question, try running a quick scenario on the simulator. I'd love to hear your feedback! 👇

ChooseAIModel.com

Stop guessing which AI model to use

Stop guessing which AI model to use