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AI Model Cost Comparison

See every current GPT, Claude, and Gemini model's monthly cost for the same usage, ranked cheapest first.

Estimated cost

$187.50/month

Per request

$0.00625

Per day

$6.25

Per year

$2,281.25

Compare across models

ModelProviderPer month
OpenAI$7.50
OpenAI$13.50
OpenAI$24.00
OpenAI$36.00
OpenAI$37.50
OpenAI$37.50
Google$46.50
Google$78.75
Anthropic$105.00
OpenAI$180.00
OpenAI$180.00
Google$180.00
OpenAI$187.50
Anthropic$210.00
OpenAI$225.00
OpenAI$240.00
Google$240.00
Anthropic$315.00
OpenAI$420.00
Anthropic$525.00
Anthropic$525.00
Anthropic$525.00
Anthropic$1,050.00

Usage

$1.25/M in · $0.125/M cached in · $10.00/M out · 400K context

How this is calculated

Providers bill input and output tokens separately, per million tokens (MTok). Cached input tokens — a repeated prompt prefix the provider recognizes — are billed at a discounted rate.

cost = (input_tokens − cached_tokens) × input_rate
     + cached_tokens × cached_rate
     + output_tokens × output_rate

Pricing is verified against provider pricing pages as of 2026-09-01. AI and cloud pricing changes frequently — confirm the current rate on the provider's own pricing page before budgeting.

Frequently asked questions

What models are included in this comparison?

Every current-generation OpenAI GPT model, every current Claude model, and every current Gemini model — ranging from budget/mini tiers to flagship reasoning models.

Why does the ranking change when I adjust token counts?

Models have different input-to-output price ratios. A model that's cheapest for input-heavy workloads (e.g. summarization) can rank differently for output-heavy workloads (e.g. long-form generation).

Does a lower cost per token mean lower total cost?

Not necessarily — it means lower cost for the same token counts. A less capable cheap model may need more tokens (retries, longer reasoning, verbose output) to complete the same task as a pricier one.

How is context window relevant to cost?

A larger context window lets you fit more history or reference material into one request without truncating, but it doesn't change the per-token price — long conversations still cost more the more tokens you resend each turn.