OpenAI GPT-4o miniHigh confidenceChecked 2026-07-13
Official OpenAI model documentation lists standard input, cached-input, and output token prices.
Estimate monthly API spend from model pricing, input tokens, output tokens, and monthly request volume. Prices change often, so treat this as scenario planning and verify official pricing before purchase.
Model paid seats, plan choice, and fixed team fees using source-tracked subscription rates.
Estimate monthly and annual GitHub Copilot subscription cost by developer count and individual plan.
Estimate team cost Team cost calculatorEstimate Cursor monthly and annual cost for individual Pro or Teams seats before rollout.
Estimate team cost Team cost calculatorEstimate Windsurf subscription cost for Pro, Max, or the tracked Teams base-plus-seat plan.
Estimate team cost Team cost calculatorEstimate the subscription cost of providing Claude Code access through tracked Pro and Max individual plans.
Estimate team cost Team cost calculatorEstimate Tabnine annual-commitment seat cost for Code Assistant and Agentic Platform plans.
Estimate team costUse editable assumptions designed around common production workloads, then compare every compatible model.
Estimate monthly LLM API cost for a customer support chatbot with repeated context, concise answers, and steady request volume.
Estimate cost Editable scenarioCompare LLM API costs for retrieval-augmented generation with document context, grounded answers, and repeat traffic.
Estimate cost Editable scenarioEstimate the cost of summarizing long documents with a large input-to-output ratio across tracked AI models.
Estimate cost Editable scenarioModel monthly LLM API spend for agent workflows that make repeated planning, tool-use, and follow-up calls.
Estimate cost Editable scenarioEstimate LLM API costs for code review prompts containing diffs, repository context, and structured review output.
Estimate cost Editable scenarioCompare API spend for short classification, moderation-routing, and intent-detection requests at high volume.
Estimate cost Editable scenarioEstimate LLM costs for extracting structured fields from text with constrained JSON output and repeat volume.
Estimate cost Editable scenarioPlan standard-rate LLM token costs for a high-volume document processing pipeline before evaluating provider batch discounts.
Estimate cost Editable scenarioCompare LLM API cost for research prompts that combine many source documents with a detailed generated answer.
Estimate cost Editable scenarioEstimate monthly API spend for personalized email drafting with short context and controlled response length.
Estimate cost Editable scenarioCompare AI model costs for categorizing, prioritizing, and routing support tickets at production volume.
Estimate cost Editable scenarioEstimate LLM API cost for a developer assistant that sends code context and returns implementation guidance or edits.
Estimate cost$0.00 per 1,000 requests
Active pricing profile: calculating...
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| Provider | Model | Profile | Monthly estimate | Per 1,000 requests | Source |
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OpenAI GPT-4o miniHigh confidenceChecked 2026-07-13
Official OpenAI model documentation lists standard input, cached-input, and output token prices.
OpenAI GPT-4oHigh confidenceChecked 2026-07-13
Official OpenAI model documentation lists standard input, cached-input, and output token prices.
OpenAI gpt-5.6-solHigh confidenceChecked 2026-07-13
Official OpenAI model documentation lists standard pricing and the higher rate applied when input exceeds 272,000 tokens.
OpenAI gpt-5.6-terraHigh confidenceChecked 2026-07-13
Official OpenAI model documentation lists standard pricing and the higher rate applied when input exceeds 272,000 tokens.
OpenAI gpt-5.6-lunaHigh confidenceChecked 2026-07-13
Official OpenAI model documentation lists standard pricing and the higher rate applied when input exceeds 272,000 tokens.
OpenAI gpt-5.4-miniHigh confidenceChecked 2026-07-13
Official OpenAI model documentation lists standard input, cached-input, and output token prices.
OpenAI gpt-5.4-nanoHigh confidenceChecked 2026-07-13
Official OpenAI model documentation lists standard input, cached-input, and output token prices.
Anthropic Claude Sonnet 5High confidenceChecked 2026-07-12
Introductory pricing is tracked through 2026-08-31. Standard pricing starts 2026-09-01 and is stored as future pricing.
Anthropic Claude Opus 4.8High confidenceChecked 2026-07-12
Official Anthropic standard, batch, and fast mode prices are stored. Standard pricing is the calculator default.
Anthropic Claude Sonnet 4.6High confidenceChecked 2026-07-12
Anthropic official pricing page lists Claude Sonnet 4.6 at $3 / MTok input and $15 / MTok output, with cache write and cache hit prices tracked.
Anthropic Claude Haiku 4.5High confidenceChecked 2026-07-12
Anthropic official pricing page lists Claude Haiku 4.5 at $1 / MTok input and $5 / MTok output, with cache write and cache hit prices tracked.
Google Gemini 2.5 ProHigh confidenceChecked 2026-07-12
Gemini 2.5 Pro uses the <=200k token standard tier by default and automatically switches to the >200k tier in the calculator. Output price includes thinking tokens.
Google Gemini 2.5 FlashHigh confidenceChecked 2026-07-12
Gemini 2.5 Flash standard text/image/video input, audio input, output including thinking tokens, context caching, and cache storage prices are tracked.
Google Gemini 2.5 Flash-LiteHigh confidenceChecked 2026-07-12
Official stable Gemini 2.5 Flash-Lite pricing is tracked. Standard text/image/video pricing is the calculator default.
Google Gemini 2.5 Flash-Lite PreviewMedium confidenceChecked 2026-07-12
Preview model retained for historical/source tracking. Use stable Gemini 2.5 Flash-Lite for default estimates unless the preview model is specifically required.
DeepSeek deepseek-v4-proHigh confidenceChecked 2026-07-12
DeepSeek V4 Pro defaults to cache-miss input pricing. Cache-hit pricing is stored but only used when a cache-hit percentage is supplied.
DeepSeek DeepSeek V4 Flash non-thinkingHigh confidenceChecked 2026-07-12
DeepSeek V4 Flash defaults to cache-miss input pricing. Cache-hit pricing is stored but only used when a cache-hit percentage is supplied.
Anthropic Claude Fable 5High confidenceChecked 2026-07-14
Official Anthropic pricing and Fable 5 launch documentation track token rates, cache rates, context limits, availability, and refusal behavior.
Anthropic Claude Mythos 5High confidenceChecked 2026-07-14
Official Anthropic pricing, model overview, and launch documentation track Mythos 5 token rates, cache rates, limits, Project Glasswing availability, and the distinction from Fable 5 safety classifiers.
Google Gemini 3.5 FlashHigh confidenceChecked 2026-07-14
Official Gemini pricing and model detail pages are parsed independently; Models API availability is optional.
Google Gemini 3.5 Live Translate PreviewHigh confidenceChecked 2026-07-14
Official Gemini pricing and model detail pages are parsed independently; Models API availability is optional.
Google Gemini 3 Flash PreviewHigh confidenceChecked 2026-07-14
Official Gemini pricing and model detail pages are parsed independently; Models API availability is optional.
Google Gemini 3.1 Flash-LiteHigh confidenceChecked 2026-07-14
Official Gemini pricing and model detail pages are parsed independently; Models API availability is optional.
Google Gemini 3.1 Pro PreviewHigh confidenceChecked 2026-07-14
Official Gemini pricing and model detail pages are parsed independently; Models API availability is optional.
Use the calculator before launching a feature, comparing provider defaults, or deciding whether a smaller routing model can handle routine requests.
Long prompts, long responses, retries, agent loops, hidden background jobs, and sending the same context repeatedly can dominate monthly cost.
Pricing data lives in JSON so it can be updated as provider rates change. Verify model rates against official provider pages before making buying decisions.
It is a planning estimate using editable pricing data. Verify official provider pricing before making a purchase decision.
Request volume, output length, retries, long system prompts, context stuffing, and using premium models for routine tasks usually drive spend.
Route simple requests to cheaper models, cache repeated context, cap output tokens, and measure cost by feature instead of only by provider.