How many words is 1,000 tokens?

In English prose, 1,000 tokens is approximately 750 words (or 4,000 characters). Code and JSON typically use slightly more tokens per character due to punctuation and indentation.

Why are output tokens more expensive than input tokens?

Input tokens can be processed in parallel during the prefill phase, whereas output tokens must be generated one by one sequentially, holding GPU KV-cache memory throughout generation.

AI & LLM API Token Cost Calculator

Estimate token counts and compare API costs across OpenAI, Claude, Gemini & DeepSeek.

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Input (Prompt) Tokens per Call Output (Completion) Tokens per Call API Calls per Day

Optional: Paste a Prompt to Measure Live Token Count ~0 tokens

Model Pricing Comparison (Per Call, Daily & Monthly @ 30 Days)

AI Model	Input / 1M	Output / 1M	Cost per Call	Daily Cost	Monthly (30d)

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How to Use AI & LLM API Token Cost Calculator

Paste a sample prompt to measure its word/character/token count — or set your average Input Tokens, Output Tokens, and Daily API Calls using the sliders.
Compare the exact per-call, daily, and monthly cost across frontier, mid-tier, and fast models.
Toggle prompt caching or batch discounts to model real production unit economics.

How LLM Token Pricing Works for SaaS & AI Workflows

Large Language Model APIs bill separately for Input (Prompt) Tokens and Output (Completion) Tokens per 1 million tokens (1M tokens ≈ 750,000 English words, or roughly 1 token ≈ 4 characters). Output tokens typically cost 3x to 5x more than input tokens because generating tokens requires sequential autoregressive memory bandwidth on datacentre GPUs.