Gemini 2.5 Flash vs GPT-4o mini: pricing & cost comparison
On input tokens, GPT-4o mini is the cheaper of the two — 50% less per million ($0.3 vs $0.15). On output, GPT-4o mini is 76% cheaper ($2.5 vs $0.6) — and since output is usually the dominant cost driver, that gap matters more than it looks.
Side by side
| Gemini 2.5 Flash | GPT-4o mini | |
|---|---|---|
| Input / 1M tokens | $0.3 | $0.15 |
| Output / 1M tokens | $2.5 | $0.6 |
| Context window | 1,000,000 | 128,000 |
| Token-count accuracy | ±3% | exact |
| Cost — 10,000 input + 2,000 output tokens | $0.008 | $0.0027 |
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-4o mini to $0.0027. Across 100,000 requests that's a $530 swing in favour of GPT-4o mini. 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 mini 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-4o mini.
FAQ
- Is Gemini 2.5 Flash or GPT-4o mini cheaper?
- For a typical request (10,000 input + 2,000 output tokens), GPT-4o mini is cheaper — about 66% less, or roughly $530 saved per 100,000 requests. Gemini 2.5 Flash runs $0.3/$2.5 per 1M input/output tokens; GPT-4o mini runs $0.15/$0.6.
- Which has the larger context window?
- Gemini 2.5 Flash, at 1,000,000 tokens versus 128,000.
- How accurate are these token counts?
- Gemini 2.5 Flash: Approximated with o200k_base; drift typically ~3% on English and code. GPT-4o mini: Exact tokenization via the canonical OpenAI vocab (o200k_base). The dollar math itself is exact once the token count is known.