Gemini omni 1.1 Flash API pricing

What it costs on a real workload

Per 1M tokens processed, at the rates above. How the four profiles are defined.

Compare every model on these profiles →

Observed rate history

No repricing observed since this model entered our archive on 2026-08-30. When a rate moves, the change appears here and on the sitewide ticker.

What the record shows

Gemini omni 1.1 Flash has not repriced once since it entered our archive on 2026-08-30. That is the ordinary case rather than the exception: providers ship new models at lower rates far more often than they cut the price of one already in service, which is why a cheaper option usually arrives as a new name rather than as a smaller number on this page.

Against the 42 models we price, it is the 34th cheapest for retrieval-shaped work, which reads a great deal and writes little, and the 29th cheapest for content-shaped work, which does the reverse. The two are far apart, and that is the useful part: Gemini omni 1.1 Flash is relatively better value the more your workload writes and the less it reads. A single position in a table sorted one way would have told you the opposite of the truth for the other kind of work.

It charges 6.0 times more for output than for input, against a median of 5.0 times across the set. That is wider than most, so the length of the answers you ask for matters more here than it does elsewhere.

Inside Google's own lineup it is the most expensive of the 7 models we track on this workload. That is worth settling before comparing it against another vendor's flagship, because the cheaper alternatives are on the same account, behind the same key, with no migration to do.

No model we price offers a larger context window, so a request too long for Gemini omni 1.1 Flash is too long for anything we track, and the answer is to change the shape of the request rather than the model.

Google publishes no cache-read rate for it, so a prompt prefix you send on every call costs the same as text the model has never seen. On a cache-heavy workload that is a structural disadvantage against models that publish one, and it is why the agent profile above prices its whole input at the standard rate.

It accepts image input and Google publishes a tokenisation rule for it, so a scanned page can be priced honestly: about 1,032 tokens for a US Letter page at 200 DPI, before the instructions you send with it.

Its 1.05M token context window holds roughly 786,000 words of English text in a single request, or about 1,016 scanned pages at the per-page figure above. A workload that does not fit cannot run here at any price, which is a capability limit rather than a cost one.

Priced near this one

Closest to Gemini omni 1.1 Flash on a retrieval workload, cheaper and more expensive alike. Cost only; we publish no quality score.

Retrieval profile: 800k in, 200k out, 70% cached where offered.