Nano Banana 2.1 edit vs generate on Sume: same price per image by tier
Do reference images change the Nano Banana 2.1 price on Sume? The estimator reads tier and image count only: $0.075 to $0.20 per image, edit or not.
On Sume, a Nano Banana 2.1 edit with reference images costs the same as a text-to-image call at the same resolution tier: $0.075 at 0.5K, $0.10 at 1K, $0.15 at 2K and $0.20 at 4K per image. The cost estimator for this row reads the tier and the image count (n), not the number of references.
The table
| Resolution | Generate | Edit with 1 reference | Edit with 5 references | 100 edits |
|---|---|---|---|---|
| 0.5K | $0.075 | $0.075 | $0.075 | $7.50 |
| 1K | $0.10 | $0.10 | $0.10 | $10.00 |
| 2K | $0.15 | $0.15 | $0.15 | $15.00 |
| 4K | $0.20 | $0.20 | $0.20 | $20.00 |
Where edits can cost more
Not every row is flat. The docs describe ChatGPT Image 2.5 at Fal token rates, with $8 per million input image tokens and $5 per million input text tokens, so images you send in add to the bill. Nano Banana 2.1 is one price per output image. If you compare models for an edit-heavy job, read each model's pricing lines from GET /v1/images/models/{model_id}/endpoints; those lines already include the Sume margin.
curl "https://api.sume.com/v1/images/models/google/nano-banana-2.1/endpoints" \
-H "Authorization: Bearer $SUME_API_KEY"Gotchas
aspect_ratio: "auto"matches the reference; leaving the field out is not the same.- A failed edit is not billed.
- The billed amount is
usage.coston the response; reconcile againstprice x n.
Sources
Related posts
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Written by Sume