Guide

How to Estimate LLM API and Token Costs

If you’re building with AI APIs, your monthly bill can range from a few dollars to thousands depending on your provider, model choice, and usage patterns. Here’s how to estimate costs before you build.

How token pricing works

LLM providers charge per token — roughly 0.75 words for English text. Every API call has two components:

• Input tokens — The prompt, system instructions, conversation history, and any uploaded documents
• Output tokens — The generated response

Input tokens cost 3–5x less than output tokens because generating text requires more compute. A typical pricing breakdown:

Provider	Input price per M tokens	Output price per M tokens
GPT-4o	$2.50	$10.00
Claude Sonnet 4.6	$3.00	$15.00
Gemini 2.5 Pro	$1.25	$5.00
DeepSeek V3	$0.27	$1.10

Estimating your usage

The biggest mistake is underestimating how many tokens you’ll use, especially for input. A single chat session can easily consume 10,000–50,000 input tokens in context alone.

Realistic estimates by use case:

Use case	Avg tokens per call	Daily calls
Simple Q&A chatbot	500–1,000	500–5,000
Customer support assistant	2,000–4,000	200–1,000
Content generation	4,000–8,000	20–100
Document analysis	15,000–30,000	10–50

Subscription vs pay-as-you-go

Some AI providers offer flat-rate subscription plans that include a set number of API calls. These can be cheaper if your usage fits within the included allotment. The decision comes down to:

• If you use less than 60% of the included calls, pay-as-you-go is probably cheaper
• If you use more than 80%, the subscription is likely better value
• If usage fluctuates heavily (some months 10K calls, others 100K), pay-as-you-go is safer

Hidden costs to watch for

• Context caching — Repeated system prompts add up fast. Use prompt caching (available on Anthropic and some OpenAI plans) to cut input costs by up to 50%
• Retries and errors — Failed API calls still consume tokens
• Testing and iteration — Development cycles can consume significant tokens that aren’t “wasted” but do add cost
• Output length — Reviews are cheaper than long reports. Control max tokens in your API calls

Choosing a provider

There’s no universal cheapest provider — it depends on your usage pattern:

• Chat-heavy workloads — GPT-4o is competitive on speed and cost
• Long document work — Claude’s 200K context and caching can be cheaper overall
• High volume, simple tasks — DeepSeek V3 or Gemini 2.5 Pro offer the lowest per-token prices
• Mixed workloads — Consider using multiple providers routed by task type