This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Calcis
Know what your LLM calls cost before you make them.
Know exactly what every LLM API call will cost before you make it. Pre-flight cost estimation for OpenAI, Anthropic, and Google models. 25+ models tracked. Prices updated within hours of provider announcements. Works in your browser, CLI, GitHub Action, VS Code, LangChain, LlamaIndex, Vercel AI SDK, and as an MCP server for Claude Desktop and Cursor. No more bill shock. Estimate first, ship with confidence.
Hey Product Hunt! I'm Ryan, the solo developer behind Calcis.
I built this after getting surprised by LLM API bills one too many times. A prompt tweak, a model swap, a new tool call, and suddenly the invoice looks nothing like what I expected. Calcis fixes that by telling you the cost before the request goes out.
What surprised me building this is how deep the problem goes. It is not just "multiply tokens by price." Output length is unpredictable, thinking effort scales cost non-linearly, tool calls compound, and switching models mid-project can change your bill by 90%. So Calcis has a 4-layer prediction stack: an LLM predictor for precise mode, a regression model trained on 33k prompt and response pairs, a Bayesian confidence interval engine, and a heuristic fallback. You get a cost estimate with a P10 to P90 range, not just a single number.
Here is what it actually does:
Pre-flight cost estimation for 25+ models across OpenAI, Anthropic, and Google
Session simulator that models full multi-turn conversations so you see cumulative cost before committing to an architecture
Subscription quota predictor that tells you what percentage of your Claude, ChatGPT, or Gemini plan a session will consume
Model comparison that suggests cheaper alternatives. Switching to the recommended model saves 60 to 90% per prompt on average
Thinking effort slider that models reasoning cost for o3, Claude Opus, and similar models
Agentic cost forecasting that accounts for tool call overhead and follow-up reasoning
Live cost badges for READMEs, six unit converters, six workload calculators, and 20+ head-to-head model comparison pages
It works across 10 distribution channels so it fits however you already build:
Browser estimator at calcis.dev, no account needed
CLI: npx calcis
VS Code extension
Browser extensions for Chrome and Firefox with live cost overlays on ChatGPT, Claude, and Gemini
GitHub Action that posts cost breakdowns on every pull request
npm packages for LangChain, LlamaIndex, Vercel AI SDK, and MCP
1,900+ unique npm downloads before today with zero promotion.
Free to use. Happy to answer anything about how it works or what is coming next.
No comment highlights available yet. Please check back later!
About Calcis on Product Hunt
“Know what your LLM calls cost before you make them.”
Calcis was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #124 on the daily leaderboard. Know exactly what every LLM API call will cost before you make it. Pre-flight cost estimation for OpenAI, Anthropic, and Google models. 25+ models tracked. Prices updated within hours of provider announcements. Works in your browser, CLI, GitHub Action, VS Code, LangChain, LlamaIndex, Vercel AI SDK, and as an MCP server for Claude Desktop and Cursor. No more bill shock. Estimate first, ship with confidence.
Calcis was featured in Productivity (650.8k followers), Developer Tools (511.7k followers), Artificial Intelligence (467.3k followers) and GitHub (41.2k followers) on Product Hunt. Together, these topics include over 306.8k products, making this a competitive space to launch in.
Who hunted Calcis?
Calcis was hunted by Ryan Chen. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Calcis stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ryan Chen