# Calcis Pre-flight LLM API cost estimator. Calcis estimates what an LLM API call will cost before you send it. Paste a prompt, pick a model, and see token counts, cost breakdowns, and at-scale projections. ## Supported providers - OpenAI (GPT-5.4, GPT-5, GPT-4o, o3, o4-mini, and more) - Anthropic (Claude Opus 4.7, Sonnet 4.6, Haiku 4.5) - Google (Gemini 2.5 Pro, 2.5 Flash, 3.1 Pro) ## Features - Web estimator with output prediction and confidence intervals - GitHub Action for cost breakdowns as PR comments - Public REST API (Pro tier and above) - VS Code extension with status bar cost display - Chrome extension overlay for ChatGPT, Claude, and Gemini - Session cost simulator for multi-turn conversations - Model recommendation engine - 25+ model pricing comparison ## Pricing - Free: token estimates, basic forecasting, no account needed - Pro ($15/mo): LLM-assisted predictions, API access, model recommendations - Max ($29/mo): prompt compression, higher volume - Team ($40/seat/mo): pooled usage, team dashboards ## Links - Website: https://www.calcis.dev - Estimator: https://www.calcis.dev/estimator - API docs: https://www.calcis.dev/api-docs - Models: https://www.calcis.dev/models - GitHub Action: https://github.com/marketplace/actions/calcis-llm-cost-estimate ## Full model pricing table Prices are USD per 1,000,000 tokens. Context / max-output are token counts. All rows verified against provider documentation; see calcis.dev/models/ for the citation and last-verified date per model. ### Anthropic | Model | Input / 1M | Output / 1M | Context | Max output | |--------------------|-----------:|------------:|-----------:|-----------:| | Claude Opus 4.7 | $5.00 | $25.00 | 1,000,000 | 128,000 | | Claude Opus 4.6 | $5.00 | $25.00 | 1,000,000 | 128,000 | | Claude Sonnet 4.6 | $3.00 | $15.00 | 1,000,000 | 64,000 | | Claude Haiku 4.5 | $1.00 | $5.00 | 200,000 | 64,000 | | Claude Opus 4.5 | $5.00 | $25.00 | 200,000 | 64,000 | | Claude Sonnet 4.5 | $3.00 | $15.00 | 200,000 | 64,000 | | Claude Opus 4.1 | $15.00 | $75.00 | 200,000 | 32,000 | Note: Opus 4.7 applies a 1.15x tokenizer multiplier so cost forecasts reflect the retrained tokenizer emitting 1.0-1.35x more tokens than Opus 4.6 for the same text. ### Google Gemini | Model | Input / 1M | Output / 1M | Context | Long-ctx (>200K) in/out | |-------------------------------|-----------:|------------:|-----------:|------------------------:| | Gemini 3.1 Pro (preview) | $2.00 | $12.00 | 1,000,000 | $4.00 / $18.00 | | Gemini 3 Flash (preview) | $0.50 | $3.00 | 1,000,000 | - | | Gemini 3.1 Flash-Lite (prev.) | $0.25 | $1.50 | 1,000,000 | - | | Gemini 2.5 Pro | $1.25 | $10.00 | 2,000,000 | $2.50 / $15.00 | | Gemini 2.5 Flash | $0.30 | $2.50 | 1,000,000 | - | | Gemini 2.5 Flash-Lite | $0.10 | $0.40 | 1,000,000 | - | Cached-input pricing is available on every Gemini row (10% of list). ### OpenAI | Model | Input / 1M | Cached in | Output / 1M | Context | Max output | |---------------|-----------:|----------:|------------:|-----------:|-----------:| | GPT-5.4 | $2.50 | $0.25 | $15.00 | 1,050,000 | 128,000 | | GPT-5.4 mini | $0.75 | $0.075 | $4.50 | 400,000 | 128,000 | | GPT-5.4 nano | $0.20 | $0.02 | $1.25 | 400,000 | 128,000 | | GPT-5 | $1.25 | $0.125 | $10.00 | 400,000 | 128,000 | | GPT-5 mini | $0.25 | $0.025 | $2.00 | 400,000 | 128,000 | | GPT-5 nano | $0.05 | $0.005 | $0.40 | 400,000 | 128,000 | | GPT-4.1 | $2.00 | $0.50 | $8.00 | 1,047,576 | 32,768 | | GPT-4.1 mini | $0.40 | $0.10 | $1.60 | 1,047,576 | 32,768 | | GPT-4o | $2.50 | $1.25 | $10.00 | 128,000 | 16,384 | | GPT-4o mini | $0.15 | $0.075 | $0.60 | 128,000 | 16,384 | | o3 | $2.00 | $0.50 | $8.00 | 200,000 | 100,000 | | o4-mini | $1.10 | $0.275 | $4.40 | 200,000 | 100,000 | ## API Public REST endpoint: POST https://www.calcis.dev/api/v1/estimate Auth: Bearer token (API key, Pro tier or above). Request body: { "prompt": "", "model": "", "expectedOutputTokens": 500 } Response: { inputTokens, outputTokens, inputCost, outputCost, total }. Full schema and examples at https://www.calcis.dev/api-docs. ## Data freshness Calcis pricing rows are re-verified on a rolling schedule against the provider's own rate card. Each row exposes a verified_at ISO date. The same source URL is cited in the model page footer.