This is a submission for the right after the Google I/O 2026 keynote to try the new model everyone was talking about — and got hit with a small wave of confusion. I went looking for "the new Flash model" and found three of them sitting in the same dropdown, names so similar I had to read them twice:
- Gemini 3.5 Flash
- Gemini 3.1 Flash Lite
- Gemini 3 Flash Preview
Three different version numbers. All called "Flash." And when I read their price tags, I found something the keynote didn't dwell on: the gap between the cheapest and the priciest is 6×. Pick the wrong one for your workload and you don't get a slightly bigger bill — you get a 6× bigger bill, for tasks that didn't need it.
Here's the lineup decoded with real numbers, the 6× trap explained, and a decision guide for which "Flash" you should actually reach for.
💡 [Screenshot spot: the AI Studio "Model selection" panel showing all three Flash models stacked together — your proof and hero image.]
The three Flash models, decoded
Pricing is per 1 million tokens, from Google's , ). Just remember "Preview" can change or disappear.
The meta-rule: default to Lite, upgrade only when you can prove you need to. Most teams will do the opposite — grab the highest version number, ship it, and quietly overpay 6× forever.
Two cost levers nobody mentioned
The price-per-token is only half the bill. Two settings move it a lot:
1. Caching is a 10× input discount. Gemini 3.5 Flash's cached input is $0.15 vs $1.50 — ten times cheaper. If your prompts share a big fixed chunk (a system prompt, a document, a schema), caching it slashes input cost. Most people never turn it on.
2. The "Thinking level" dial controls how hard — and how expensively — the model reasons. Gemini 3.x replaces the old token-budget setting with a thinkingLevel of minimal / low / medium / high ( and AI Studio during the I/O 2026 window (Gemini 3.5 Flash GA'd May 19, 2026); verify current numbers before relying on them, as they change. Master announcement list: "100 things we announced at Google I/O 2026". I drafted this with AI assistance and verified every number against Google's docs and AI Studio myself — the analysis and screenshots are mine.
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