Gemini 2.5 Flash vs Gemini 2.5 Pro: 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 | Gemini 2.5 Pro | |
|---|---|---|
| Input / 1M tokens | $0.3 | $1.25 |
| Output / 1M tokens | $2.5 | $10 |
| Context window | 1,000,000 | 1,000,000 |
| Token-count accuracy | ±3% | ±3% |
| 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, Gemini 2.5 Pro 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.
Same family — pick on price
Moving between Gemini 2.5 Flash and Gemini 2.5 Pro is a one-line model-string change — same family, same tokenizer, nothing to re-encode. That makes this a straight cost/quality call: send the routine bulk of traffic to Gemini 2.5 Flash ($0.3/$2.5 per 1M) and reserve Gemini 2.5 Pro for the requests that visibly need its extra headroom. On the worked example above that split is worth about 75% per request — small per call, real money once you multiply by volume.
See the full breakdown on the dedicated pages for Gemini 2.5 Flash and Gemini 2.5 Pro.
FAQ
- Is Gemini 2.5 Flash or Gemini 2.5 Pro 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; Gemini 2.5 Pro runs $1.25/$10.
- Which has the larger context window?
- Both support a 1,000,000-token context window.
- How accurate are these token counts?
- Gemini 2.5 Flash: Approximated with o200k_base; drift typically ~3% on English and code. Gemini 2.5 Pro: Approximated with o200k_base; drift typically ~3% on English and code. The dollar math itself is exact once the token count is known.
Both prices are computed from tokenmath's verified pricing table. Rates sourced from ai.google.dev, verified 2026-05-09. Vendor pricing changes often — confirm before you commit.