HedraImage to imageComing soon
nano-banana-2.1
nano-banana-2.1 is an image to image tool from Hedra that runs in the background and returns images. Coming soon: listed with its price, not yet open to runs.
This tool is listed but not yet available to run.
Price pendingPricing
Price pending.
Limits
- Runs
- In the background
- Returns
- image
- Longest queue wait
- 3600s
- Run deadline
- 1800s
- Largest inline input
- 1024 KB
- Largest input file
- 500 MB
- Largest output
- 4768 MB
- Outputs per run
- 16
Input
| Field | Kind | Default | Description |
|---|---|---|---|
prompt required | text | — | Generation prompt. |
resolution required | one of 1K, 2K, 4K | — | Output resolution. |
aspect_ratio required | one of adaptive, 16:9, 9:16, 1:1, 21:9, 4:3, 3:4, 3:2, 2:3, 5:4, 4:5, 1:4, 4:1, 1:8, 8:1 | — | Output aspect ratio. 'adaptive' lets the model size the output itself — matching the source image when you pass one. |
images | JSON | — | Images to edit or blend, at most 10 high-fidelity objects and 4 characters. 1 to 14 images, each at most 30 MB. |
num_outputs | one of 1 | 1 | Number of outputs generated per job. Only 1 is supported. |
image_search | true or false | false | Let the grounding search return images as well as text, so the model sees what it found rather than only reading about it. Turning this on grounds the generation whether or not google_search is also set. |
google_search | true or false | false | Ground the generation in live Google Search results, so a prompt about current events or real-world specifics draws on what the web says now. Grounded generations cost more than ungrounded ones. |
enhance_prompt | true or false | false | Rewrite the prompt before generation. An LLM expands it into a fuller description and the model receives that text instead of the submitted one; the result's `prompt` reports what ran. |
thinking_level | one of minimal, high | — | How much the model plans before it draws. Omit for the model's own default ('minimal'); 'high' reasons further at the cost of latency. |
Same request in code
curl https://api.spiral.ai/v1/runs \
-H "Authorization: Bearer $SPIRAL_API_KEY" \
-H "Content-Type: application/json" \
-H "Idempotency-Key: $(uuidgen)" \
-d '{
"provider": "hedra",
"model": "nano-banana-2.1",
"input": {
"prompt": "<prompt>",
"resolution": "1K",
"aspect_ratio": "adaptive"
}
}'