Is Gemini 2.5 Pro or GPT-4o cheaper?

For a typical request (10,000 input + 2,000 output tokens), Gemini 2.5 Pro is cheaper — about 28% less, or roughly $1250 saved per 100,000 requests. Gemini 2.5 Pro runs $1.25/$10 per 1M input/output tokens; GPT-4o runs $2.5/$10.

Which has the larger context window?

Gemini 2.5 Pro, at 1,000,000 tokens versus 128,000.

How accurate are these token counts?

Gemini 2.5 Pro: Approximated with o200k_base; drift typically ~3% on English and code. GPT-4o: Exact tokenization via the canonical OpenAI vocab (o200k_base). The dollar math itself is exact once the token count is known.

Gemini 2.5 Pro vs GPT-4o: pricing & cost comparison

On input tokens, Gemini 2.5 Pro is the cheaper of the two — 50% less per million ($1.25 vs $2.5). Both charge $10 per million output tokens.

Side by side

	Gemini 2.5 Pro	GPT-4o
Input / 1M tokens	$1.25	$2.5
Output / 1M tokens	$10	$10
Context window	1,000,000	128,000
Token-count accuracy	±3%	exact
Cost — 10,000 input + 2,000 output tokens	$0.0325	$0.045

What a real request costs

Take a representative turn — 10,000 input + 2,000 output tokens. Gemini 2.5 Pro comes to $0.0325, GPT-4o to $0.045. Across 100,000 requests that's a $1250 swing in favour of Gemini 2.5 Pro. To run the numbers on your actual prompt, paste it into the calculator and toggle Compare across all models.

Which should you pick?

These are different vendors, so a switch means a different API and a slightly different tokenizer — budget a small calibration buffer. GPT-4o give exact counts; the others land within a few percent. See the full breakdown on the dedicated pages for Gemini 2.5 Pro and GPT-4o.

FAQ

Is Gemini 2.5 Pro or GPT-4o cheaper?: For a typical request (10,000 input + 2,000 output tokens), Gemini 2.5 Pro is cheaper — about 28% less, or roughly $1250 saved per 100,000 requests. Gemini 2.5 Pro runs $1.25/$10 per 1M input/output tokens; GPT-4o runs $2.5/$10.
Which has the larger context window?: Gemini 2.5 Pro, at 1,000,000 tokens versus 128,000.
How accurate are these token counts?: Gemini 2.5 Pro: Approximated with o200k_base; drift typically ~3% on English and code. GPT-4o: Exact tokenization via the canonical OpenAI vocab (o200k_base). The dollar math itself is exact once the token count is known.