MiniMax H3-Image vs Seedream 5.5 vs Nano Banana 2.1 vs GPT-Image-2.6
Four image models, same prompts, same scoring: MiniMax H3-Image is the cheapest with the highest resolution, but Nano Banana 2.1 wins on Polish text.
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Two new image models from China arrived within two days: Seedream 5.5 from ByteDance on 9 November, and MiniMax H3-Image on 10 November. I tested both with the same set of prompts I had already used on Google’s Nano Banana 2.1 and OpenAI’s GPT-Image-2.6. That gives me a rare setup: four models, identical prompts, one counting method. Below is the comparison in six categories, each backed by numbers from my own tests.
MiniMax H3-Image vs Seedream 5.5, Nano Banana 2.1 and GPT-Image-2.6: summary table
| Category | MiniMax H3-Image | Seedream 5.5 | Nano Banana 2.1 | GPT-Image-2.6 |
|---|---|---|---|---|
| Polish text, 5 prompts (389 characters), errors per run | 13 (14, 10, 15) | 3 | 0 and 0 | 1 and 0 |
| Short slogans, 10 x 3, images with no errors | 17/30 | 27/30 | 30/30 | 10/10 (10 x 1) |
| Face from 3 photos, ArcFace, average of 10 images | 0.573 | 0.632 (5 images) | 0.508 | 0.729 |
| Transparent background (my test) | none, 0/5 | 10/10 RGBA | not tested | not tested |
| Highest resolution at the providers I used | up to 20 MP (4K = about 16 MP) | 2K | 4K | - |
| Price per image in my tests | $0.023 (2K) | $0.035 (2K, WaveSpeedAI) | $0.050 (2K) | $0.044 (1024×1024, medium) |
| Time at 2K | 13-17 s | 21-28 s | 13-19 s | 24-43 s |
| Reference images (documentation) | up to 16 | - | up to 14 | up to 16 |
| Open weights | yes, but the licence excludes the EU, UK, South Korea and USA | no | no | no |
The rivals’ prices are the cost I read from the cost fields in my 10 November tests (Nano Banana 2.1 at 2K via OpenRouter, GPT-Image-2.6 Sunburst medium at 1024×1024), plus WaveSpeedAI’s published price for Seedream 5.5. Resolutions and reference counts for the rivals come from provider catalogues (WaveSpeedAI, FlashBoards) as of 10 November. A hyphen means I did not check.
On the open weights: the licence excludes the EU, the UK, South Korea and the USA. Readers elsewhere (for example India, Canada or Australia) may run the weights under the licence terms, and companies with over 1 million USD annual revenue or hosted services need separate permission.
1. Text with Polish diacritics: Nano Banana 2.1 wins
I used five prompts: a bakery sign, a poster, a book cover, a menu and a board with a pangram. Nano Banana 2.1 and GPT-Image-2.6 wrote almost flawlessly, Seedream 5.5 made 3 errors, and H3-Image averaged 13. H3’s most common mistake was “zl” instead of “zł” (the Polish currency sign), in every single price. Details are in my write-up, MiniMax H3-Image and Polish text.
2. Face consistency from reference photos: GPT-Image-2.6 wins
Same setup for every model: 10 prompts (studio portrait, street at night, music studio, train platform, pencil drawing and others) and the same 3 photos of Waco, who agreed to the use of his likeness in my tutorials. I measure face similarity with ArcFace, identically for each model. GPT-Image-2.6 scored 0.729, Seedream 5.5 0.632, H3-Image 0.573 and Nano Banana 2.1 0.508. H3 keeps the character and clothing consistent, but the face is “similar”, not “the same”.
One important caveat. On the first run H3-Image scored 0.273, which means a stranger. It turned out I had sent phone photos without applying the EXIF rotation, so the model received faces lying on their side. Other APIs rotated the photos on their own; this one did not. After rotating them, the score was 0.573.
3. Transparent background (PNG with alpha): Seedream 5.5 wins
H3-Image has no transparent background at all (the documentation lists it as unsupported, and in my test it managed 0 out of 5). Seedream 5.5 returned 10 out of 10 files with a real alpha channel, although glass is not see-through. H3 won’t work for product cutouts unless you remove the background with a separate tool.
4. Image editing: it depends how you do it
A single edit from the original in H3-Image is very good: I moved a serum bottle into six scenes and the label stayed identical 6 times out of 6. Chain editing is worse, meaning an edit of the result of a previous edit. After 2-3 rounds a texture appears on the label paper, and after 5 rounds the image looks oversharpened. In the same test Seedream 5.5 got through 8 rounds cleanly. The full description is in my article on product editing in MiniMax H3-Image.
5. Resolution and multiple reference images: H3-Image wins
In this set H3-Image has no competition here. It gives you 16 MP straight away, with no upscaler, in 22-24 s and for $0.034 in launch week. The test with 16 references (an empty room plus 15 objects) produced a living room with all 15 objects in both attempts. More in my articles on 4K for print and on 16 references.
6. Price and speed: H3-Image wins
$0.023 for 2K is the lowest of the four, and 13-17 seconds matches Nano Banana 2.1. GPT-Image-2.6 at high quality needed up to 43 s.
Which one to pick
- Graphics with Polish text: Nano Banana 2.1, or GPT-Image-2.6 as an alternative.
- A specific face from a few photos: GPT-Image-2.6.
- A product on a transparent background: Seedream 5.5 (covered in my Seedream 5.5 hub).
- Large images, print, scenes with many objects, one product in many settings, on a budget: MiniMax H3-Image.
All my H3-Image results are collected in the MiniMax H3-Image hub, and I covered Nano Banana 2.1 in a separate article.
Sources
- My own MiniMax H3-Image test of 10 Nov 2026 via the API (cost taken from the cost field), text checked at enlarged size, ArcFace with insightface buffalo_l.
- My own tests of Seedream 5.5, Nano Banana 2.1 and GPT-Image-2.6 from 9-10 Nov 2026 on the same prompts; the face set comes from the model test on Waco’s photos.
- MiniMax: Image Generation Guide
- MiniMax: API pricing (10 Nov 2026)
Checked: 10 Nov 2026.
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