AI Desk · AI FingerprintingNew arrival
Why high: an exact fingerprint shared with 21 models that declare the same family, without a second signal of a different kind yet.
Google: Nano Banana 2.1 is Google's model. Its measured tokenizer sits with the Gemini group, which is evidence that it builds on the Gemini tokenizer. Tokenizer reuse is normal engineering, open vocabularies travel between labs, and this says nothing against Google's authorship of the model itself.
| We checked | What we found | Where it came from |
|---|---|---|
| How it counts tokens | Counts every one of the 50 test strings exactly like 21 other models | tk_59ca250f |
| How its API is set up | A combination of settings no other listing in the catalogue uses | api_660293ae |
| How much it can read and write | Reads up to 65,536 tokens at onceOpenRouter's listing shows 58,982 output tokens, which is 90% of the context window, the figure it carries where the provider declares no maximum. | its own listing |
| Whether it thinks before answering | Reasons when asked to, at high, minimal, minimal by default | its own listing |
| Who served our requests | Google AI Studio | we measured it, 8 October 2026 |
Click a row to open the full comparison.
We sent Google: Nano Banana 2.1 fifty short pieces of text and recorded what each one cost it in tokens. The bars below are those costs. Two models built on the same tokenizer produce the same bars; a model built on a different one produces a different set, which is what makes this a fingerprint.
Overhead subtracted: 1 prompt tokens.
Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization,...
Supported parameters
include_reasoningmax_tokensreasoningreasoning_effortresponse_formatseedstructured_outputstemperaturetool_choicetoolstop_p
defaults: {}
