Nano Banana 2.1 vs Nano Banana Pro on Sume: $0.10 vs $0.1875

Nano Banana 2.1 bills $0.10 at 1K on Sume; Pro bills $0.1875. 2.1 adds 8:1, 4:1, 1:4 and 1:8 ratios; both list 0.5K to 4K and up to 10 references.

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Nano Banana 2.1 is cheaper and lists more aspect ratios; Nano Banana Pro costs 1.875 times as much at 1K. On Sume, google/nano-banana-2.1 lists $0.08 per image at 1K (billed $0.10) and google/nano-banana-pro lists $0.15 (billed $0.1875). Both accept 0.5K, 1K, 2K and 4K, and both accept edit references.

Catalog comparison

Values come from the Sume repo's catalog; 4K on Pro is charged above the listed default rate, per the catalog note, and Sume scales admission for the other tiers.

Sume image catalog rows (list from the Sume repo, billed = list x 1.25), read 2026-10-13
Itemgoogle/nano-banana-2.1google/nano-banana-pro
List per image (1K)$0.08$0.15
Billed per image (1K)$0.10$0.1875
Resolutions0.5K, 1K, 2K, 4K0.5K, 1K, 2K, 4K
Ratios15 incl. 8:1, 4:1, 1:4, 1:811 up to 21:9
4:5 portraitYesYes
n per call1 to 41 to 4

Draft with one, finish with the other

A two-stage run is cheap to set up because both ids share a request shape. Draft on 2.1 at 0.5K, pick a winner, and rerun that prompt on Pro at the final tier if the result needs it. Whether Pro looks better for your prompts is a test to run, not a number to quote.

The helper below returns the billed estimate for a plan from list prices; it is arithmetic only.

LIST = {"google/nano-banana-2.1": 0.08, "google/nano-banana-pro": 0.15}

def billed(model, n):
    return round(LIST[model] * 1.25 * n, 4)

draft = billed("google/nano-banana-2.1", 20)
final = billed("google/nano-banana-pro", 3)
print(draft, final, round(draft + final, 4))

Caveat

These are 1K default rates. Check the per-model endpoints record and the rate card before you size a 2K or 4K run.

Sources

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