Nano Banana reference limits: Gemini slots vs Sume input_references
Google counts Nano Banana references by tier and by object versus character. Sume exposes one input_references range per row. How to read it and what to send.

Google splits reference images into slots by kind. Its Gemini image docs (read 2026-10-06) give the Pro model 6 object references and 5 character references, the Flash model 10 object references and 4 character references, and a Lite tier 14 object references. Sume does not copy that split. Each Sume row publishes one input_references range, and you read the maximum from the catalog.
The Sume rows for Nano Banana are google/nano-banana-2 and google/nano-banana-pro. Read the range for each row before you plan a reference set.
Two ways of counting
| Where | How it counts | What you read |
|---|---|---|
| Gemini API, Pro | 6 object + 5 character references | The model page |
| Gemini API, Flash | 10 object + 4 character references | The model page |
| Gemini API, Lite | 14 object references | The model page |
| Sume, most edit rows | One array, 10 max | input_references descriptor |
| Sume, GPT Image 2.5 rows | One array, 16 max | input_references descriptor |
| Sume, Ideogram 4.5 | One array, 5 max, first is the image edited | input_references descriptor |
What changes in the call
On Sume you send a plain list of image_url entries under input_references. There is no field that labels an entry as an object or a character. If the identity of a person matters, say so in the prompt and put that image first.
Every URL must be public HTTPS. Sume rejects localhost, private-network and non-HTTPS URLs before it submits the job, so a link that only works on your network fails early.
How to pick the number to send
- Send fewer than the maximum. More references means more things for the model to blend, and each one adds weight to the prompt.
- Put the most important image first. Ideogram 4.5 edits the first image; for other rows, name the image to change in the prompt.
- Name each reference's job in the prompt, such as the product to keep, the style to match, the scene to place it in.
- If the call returns
400 unsupported_parameter, the row does not take that field. Read its descriptors again.
A note on provenance
Google's docs state that all outputs carry SynthID, a watermark. Sume's docs do not describe how Sume handles that for Nano Banana rows, so do not promise your client a particular result when you pass the files on.
Sources
Related posts
More in Models
- Native 4K AI video API: LTX-2.5 claims 4K, what Sume offers instead
LTX-2.5 is listed up to 4K but is not in Sume's catalog. Sume's 4K options are Gemini Omni Flash 1.1 and MiniMax H3 4K upscales. Limits and per-second prices.
- New AI video models since February 2026: dates and which Sume lists
Kling 3.0, Seedance 2.5, MiniMax H3 and LTX-2.5 launched in 2026. Release dates, length limits and which of them Sume's video catalog lists today.
- Retired AI model id to Sume id: GPT Image, Gemini and Sora lookup
One lookup table that maps retired gpt-image-1, gemini-2.5-flash-image and sora-2 ids to Sume ids, with dates, so a failing call tells you what to switch to.
- Seedance 2.5 API: Seed blog says soon, BytePlus says live
Two ByteDance pages disagree on Seedance 2.5 API access. Here is what each says, and the seedance-2.5 id that runs on Sume's video router today.
Written by Sume