Cheapest Sume image models that take a reference photo
Reference edits start at $0.025 per image on Sume. Ranked list of every catalog model that accepts input_references, with reference limits and prices.
The cheapest reference edits on Sume are Qwen Image and Grok Imagine at $0.025 per image, then Seedream 4 at $0.0325 and Flux 2 Pro at $0.0375 (catalog read 2026-10-03). GPT Image 2.5 takes 16 references, the most of any row, and its medium square estimate is $0.0165, which is cheaper than any of them at that quality. Five rows are text-only: Imagen 4 Fast and Ultra, Recraft V4, Qwen Image Max and Higgsfield Soul accept no references.
Ranked list
The list comes from the catalog descriptors and the per-image endpoint prices (list x 1.25), read 2026-10-03. GPT Image 2.5 prices are repo estimates by quality and size, not billed figures.
| Rank | Model | Price per image | Max references |
|---|---|---|---|
| 1 | Qwen Image | $0.025 | 10 |
| 1 | Grok Imagine | $0.025 | 10 |
| 3 | Seedream 4 | $0.0325 | 10 |
| 4 | Flux 2 Pro | $0.0375 | 10 |
| 4 | Ideogram 4.5, low quality | $0.0375 | 5 |
| 6 | Seedream 5 Lite | $0.04375 | 10 |
| 7 | Seedream 4.5 | $0.05 | 10 |
| 8 | Flux 2 Flex | $0.0625 | 10 |
| 9 | GPT Image 2.5, high (default estimate) | $0.0659 | 16 |
| 10 | Ideogram V3 | $0.075 | 10 |
| 10 | Ideogram 4.5, medium (default) | $0.075 | 5 |
| 12 | Nano Banana 2 | $0.10 | 10 |
| 13 | Nano Banana Pro | $0.1875 | 10 |
Where GPT Image 2.5 fits
GPT Image 2.5 is the only row where quality sets the price. A square at low quality is an estimated $0.0074, medium $0.0165, high $0.0659, xhigh $0.1171 and max $0.2634. It also takes background and mask_url, so it is the row for masked edits and transparent output. The default quality is high, which is why a single catalog figure of $0.0659 shows.
Edit request
Send the photo as input_references and ask for one change.
curl -s https://api.sume.com/v1/images \
-H "Authorization: Bearer $SUME_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "qwen/qwen-image", "input_references": [{"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}}], "prompt": "Keep the person and pose, change the background to a sunny balcony"}' What to test first
Price tells you little about edit fidelity. Run your three hardest pictures through the top three rows and compare the results by eye.
- Does the face or product stay the same?
- Does it follow the one change you asked for?
- How many takes did you need?
Sources
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