Gemini 2.5 Flash · Google
Google's Gemini 2.5 Flash. High speed + 1 million token context. Excellent for analysis of long documents.
About Gemini 2.5 Flash
Google's Gemini 2.5 Flash. High speed + 1 million token context. Excellent for analysis of long documents.
Where it shines: 1M context · Google speed · STEM.
How to use Gemini 2.5 Flash
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1
Type or upload
Type what you want in the box above — or upload the file if the tool asks for one.
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2
Generate
Click the main button. Wait 2-30 seconds depending on the model and input size.
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3
Download or share
Download the result or share the direct link. No watermark, ready to use.
Frequently asked questions
How much does it cost to use Gemini 2.5 Flash?
Gemini 2.5 Flash is a Pro model: it costs 20 tokens per use (~$0.10 real cost for us). You need a Pro plan ($9/month → 15,000 tokens) or a one-shot pack.If you already have tokens in the free account, you can also spend them directly.
How many uses of Gemini 2.5 Flash are included in the Pro plan?
Pro ($9/month) gives you 15,000 recurring tokens, at 20 tokens per Gemini 2.5 Flash use, that's ~750 full uses per cycle. If you run out, one-shot packs (5,000 / 25,000 / 80,000 tokens) add to the balance without expiring before one year.
What makes Gemini 2.5 Flash special?
Google trains border models in chat (Gemini), image (Image), video (Veo) and music (Lyria), with emphasis on multimodality and STEM reasoning. Its specific strengths are: 1m context, google speed and stem. It accepts images as input (multimodal) as well as text — useful for describing captures, reading graphs or solving problems from a photo.
How fast does Gemini 2.5 Flash respond?
Gemini 2.5 Flash is one of the fastest models in the catalog: typical responses in 2-5 seconds, the actual time also depends on the length of the prompt and the load of the datacenter — models with huge context take longer when you enter very long texts.
How do I use Gemini 2.5 Flash on ia.gratis?
You can use Gemini 2.5 Flash from /chat/ by selecting Gemini 2.5 Flash in the picker, or via the REST API with `model=gemini-2-5-flash` in the body of the POST. Quick summary: gemini fast with 1M context.The internal model identifier is `gemini-2-5-flash` — useful when integrating via API.