Qwen Image Max at $0.09375 vs Nano Banana 2.1 at $0.10: 100 images
On Sume, Qwen Image Max costs $0.09375 per image and Nano Banana 2.1 costs $0.10 at 1K. 100 images are $9.38 or $10.00. Ratios, resolution tiers and the pick.
The short answer
Qwen Image Max is 6.25% cheaper per image than Nano Banana 2.1 at 1K on Sume: $0.09375 against $0.10, a gap of $0.00625. For 100 images that is $9.375 (shown as $9.38) against $10.00. The saving is $0.625 per 100 images, small enough that the choice should turn on features, not price.
Side by side
Both rows are in the Sume catalog read on 2026-10-09. Nano Banana 2.1 has a resolution parameter with tiers, while Qwen Image Max is a flat per-image row at default options. Ratio lists come from the repo's image catalog.
| Item | qwen-image-max | nano-banana-2.1 |
|---|---|---|
| Price per image (default options) | $0.09375 | $0.10 at 1K |
| Other tiers | One price listed | $0.075 at 0.5K, $0.15 at 2K, $0.20 at 4K |
| Named aspect ratios | 13 (1:1, 16:9, 9:16, 4:3, 3:4, 4:5, 5:4, 3:2, 2:3, 21:9, 9:21, 1:2, 2:1) | 15 incl. auto, with 4:1, 1:4, 8:1 and 1:8 |
| 100 images | $9.375 | $10.00 |
Where the price stops mattering
If you need a tier below 1K, Nano Banana 2.1 at 0.5K is $0.075, cheaper than Qwen Image Max at 100 images for $7.50 against $9.375. If you need 4K, the price list gives Qwen Image Max one price and no 4K tier, while Nano Banana 2.1 lists one at $0.20. If you need an extreme banner such as 8:1, only the Banana row lists it of the two.
Qwen Image Max does list 21:9 and 9:21, which Nano Banana 2.1 also covers, so ultrawide work is open to both.
How to decide
Run the same 10 prompts through both models and keep the cost with each. The price gap is 0.625 cents per image, so for 100 images the difference is 62.5 cents. Any quality difference you can see in the ten pairs is worth more than that.
Check resolution too: confirm in the model list which sizes each model accepts before you compare, so that you are not comparing a small output with a large one.
How to decide
Run the same ten prompts on both and compare by eye. Ten images cost $0.9375 on Qwen Image Max and $1.00 on Nano Banana 2.1, so the test is cheap. Pin the model id in your code instead of sume/auto, since Auto does not disclose which family ran, and read GET /v1/images/models/{model_id}/endpoints to confirm the parameters you plan to send.
Latency and cost are the two numbers that do not change with taste, so record both. Each response carries usage.cost, and the job status shows when the work finished. A model that is 0.625 cents cheaper but takes twice as long may still be the wrong pick for an interactive tool, and the right one for an overnight batch.
Keep the prompt, the seed policy and the size identical across the two runs. Otherwise the comparison measures your changes rather than the models.
Sources
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