Google: Gemini 2.5 Flash API Pricing
Google: Gemini 2.5 Flash costs $0.300 per 1M input tokens and $2.50 per 1M output tokens (cache reads: $0.030). Context window: 1.0M. Prices verified 2026-10-21 · source
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Rebuilt daily from our snapshot archive — the chart appears once a model has 5+ snapshots of history.
From our own daily snapshot archive — independent of provider announcements.
Intelligence measures reasoning/knowledge/coding benchmarks. A high score with a low blended price = value pick; check the value chart to see where this model lands.
Token economics
| Token type | Price | vs base input |
|---|---|---|
| Standard input | $0.300 | — |
| Cache read | $0.030 | −90% |
| Cache write (5m) | $0.083 | -72% |
| Output | $2.50 | — |
| Web search tool | $14/1k searches | — |
Prompt caching stores repeated context server-side: reads cost far less, but writes carry a one-time premium.
Higher effort = deeper thinking = more reasoning tokens billed as output.
Training data ends here — newer events require retrieval or web search.
What would Google: Gemini 2.5 Flash cost you per month?
| Workload | Requests/mo | Avg tokens (in/out) | Est. monthly cost |
|---|---|---|---|
| Light chatbot | 10,000 | 800 / 400 | $12.40 |
| Coding agent | 5,000 | 8,000 / 2,000 | $37.00 |
| RAG pipeline | 30,000 | 4,000 / 500 | $73.50 |
| Doc summarizer | 2,000 | 20,000 / 1,000 | $17.00 |
Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.
About Google: Gemini 2.5 Flash
Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater...
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Frequently asked questions
How much does Google: Gemini 2.5 Flash cost?
Google: Gemini 2.5 Flash costs $0.300 per 1M input tokens and $2.50 per 1M output tokens; cached input tokens cost $0.030 per 1M. Verified 2026-10-21 — provider source.
What is the context window?
1.0M tokens, with up to 66K output tokens per response. That's roughly 1311 pages of text in a single request.
Does it support prompt caching?
Yes — cached input is $0.030/1M, about 90% cheaper than standard input. Agents and RAG workloads with repeated context benefit most.
What's a cheaper alternative?
ScaleDown: Summarize saves about 97% on a typical workload with comparable quality.
Official resources
- Google: Gemini 2.5 Flash on OpenRouter — live endpoint, pricing source of record.
- Artificial Analysis leaderboard → — independent intelligence and performance rankings.
- Gemini docs → — first-party model specifications and limits.
- LMArena leaderboard → — independent human-preference rankings.
- Shred your current bill — paste a CSV and see if switching saves money.