Is Gemini 2.5 Flash or GPT-5 cheaper?

For a typical request (10,000 input + 2,000 output tokens), Gemini 2.5 Flash is cheaper — about 75% less, or roughly $2450 saved per 100,000 requests. Gemini 2.5 Flash runs $0.3/$2.5 per 1M input/output tokens; GPT-5 runs $1.25/$10.

Which has the larger context window?

Gemini 2.5 Flash, at 1,000,000 tokens versus 400,000.

How accurate are these token counts?

Gemini 2.5 Flash: Approximated with o200k_base; drift typically ~3% on English and code. GPT-5: Exact tokenization via the canonical OpenAI vocab (o200k_base). The dollar math itself is exact once the token count is known.

Gemini 2.5 Flash vs GPT-5: pricing & cost comparison

On input tokens, Gemini 2.5 Flash is the cheaper of the two — 76% less per million ($0.3 vs $1.25). On output, Gemini 2.5 Flash is 75% cheaper ($2.5 vs $10) — and since output is usually the dominant cost driver, that gap matters more than it looks.

Side by side

	Gemini 2.5 Flash	GPT-5
Input / 1M tokens	$0.3	$1.25
Output / 1M tokens	$2.5	$10
Context window	1,000,000	400,000
Token-count accuracy	±3%	exact
Cost — 10,000 input + 2,000 output tokens	$0.008	$0.0325

What a real request costs

Take a representative turn — 10,000 input + 2,000 output tokens. Gemini 2.5 Flash comes to $0.008, GPT-5 to $0.0325. Across 100,000 requests that's a $2450 swing in favour of Gemini 2.5 Flash. 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-5 give exact counts; the others land within a few percent. See the full breakdown on the dedicated pages for Gemini 2.5 Flash and GPT-5.

FAQ

Is Gemini 2.5 Flash or GPT-5 cheaper?: For a typical request (10,000 input + 2,000 output tokens), Gemini 2.5 Flash is cheaper — about 75% less, or roughly $2450 saved per 100,000 requests. Gemini 2.5 Flash runs $0.3/$2.5 per 1M input/output tokens; GPT-5 runs $1.25/$10.
Which has the larger context window?: Gemini 2.5 Flash, at 1,000,000 tokens versus 400,000.
How accurate are these token counts?: Gemini 2.5 Flash: Approximated with o200k_base; drift typically ~3% on English and code. GPT-5: Exact tokenization via the canonical OpenAI vocab (o200k_base). The dollar math itself is exact once the token count is known.