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GPT Token Calculator

Turn GPT token counts into a dollar estimate and compare OpenAI's models for the same workload.

CalculatorConvert tokens to cost · live workload estimate
Typical workloads
Estimate tokens from text
≈ 0 tokens

Rough estimate from character count; tokenizers vary by model, language, and content.

Cost by model
Selected model

GPT-5.6 Terra

$0.80per request

$0.765 more than GPT-6 Luna · 22.9× the cheapest

Model selection

GPT-5.6 Terra: $2.00 input / $12.00 output per 1M tokens.

How this GPT Token Calculator works

How GPT counts tokens

GPT splits text into tokens with byte-pair encoding, so one token is roughly four English characters — but code, punctuation, emoji, and non-English text break that ratio, and even whitespace counts. For exact numbers use the tiktoken library or read the usage field the API returns. The part that surprises budgets: your system prompt, the full conversation history, and any retrieved context are re-sent as input tokens on every call, so a chat or agent feature's input grows turn over turn.

Choosing the right GPT model

Treat the lineup as a ladder. GPT-6 Astra is the premium tier for demanding work; GPT-6 Sol balances capability and cost; and GPT-6 Luna is the lowest-cost tier for high-volume jobs such as classification, extraction, and routing. The verified GPT-5.6 and GPT-5.4 families remain available for workloads pinned to those model IDs. Because output is priced well above input on every tier, anything that generates long answers is dominated by output cost — switch the model in the calculator above to compare the same workload across tiers before you commit.

What this estimate leaves out

The figure is a standard list-price baseline. It excludes cached-input discounts, the Batch API (much cheaper for non-urgent jobs), priority and flex tiers, image and audio tokens, and tool-call fees. Size your feature here, then reconcile against real OpenAI usage once traffic is live.

Examples

Document summaries

GPT-5.6 Terra · 30,000 input → 800 output tokens per run. Small output, so input dominates the bill.

Bulk classification

GPT-5.6 Luna · 1,000,000 short messages. Input-heavy with tiny output on the lowest-cost tier.

Complex reasoning

GPT-6 Astra · 5,000 input / 2,000 output tokens. Long output on the premium tier — output cost leads.

FAQ

Are these AI costs exact?

They are estimates based on public token prices. Your bill can change with cached tokens, batch discounts, image or audio usage, taxes, provider credits, and model-specific rules.

Which currency does the calculator use?

All calculators use USD by default because major AI providers publish API pricing in USD.

How are GPT tokens counted?

OpenAI uses byte-pair encoding. As a rough guide one token is about four English characters, but code, symbols, and other languages differ. For exact counts use the tiktoken library or the usage field the API returns.

Why do GPT output tokens cost more than input tokens?

Generating tokens is more compute-intensive than reading them, so OpenAI prices output higher on every model. Features that produce long responses are driven mostly by output cost.

Which GPT model is cheapest?

Within the verified OpenAI lineup, GPT-6 Luna has the lowest standard short-context token rates and suits high-volume, low-complexity work. Reserve GPT-6 Astra for tasks that genuinely need its stronger capability.