Bria FIBO 2.0 Text-to-Image creates images from text prompts, with an optional reference image, flexible aspect ratios, and advanced structured prompting for product visuals, marketing assets, creative content, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
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$0.04per run·~25 / $1
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A young male orbital station engineer standing inside a vast ring-shaped space habitat, wearing a fitted dark technical jumpsuit with silver fasteners and subtle illuminated seams. She holds a transparent diagnostic tablet in one hand while adjusting a wall-mounted control module with the other. Behind her, curved windows reveal Earth below, while cables, instrument panels, warning lights, docking equipment, and brushed metal structures create dense sci-fi detail. Realistic skin texture, highly detailed hands, glass reflections, metallic surfaces, subtle blue and amber lighting, grounded science-fiction realism.
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A young female knight standing inside a medieval armory, wearing realistic silver plate armor over dark blue fabric, one hand resting on an engraved longsword. Chainmail, leather belts, metal buckles, weapon racks, and banners surround her. Cinematic Western fantasy realism, detailed armor and fabric textures.
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A young female jewelry designer seated at a fine workbench, wearing a dark blouse and magnifying glasses pushed onto her forehead. She holds an elegant silver pendant with precision tweezers. Gemstones, tiny chains, engraving tools, velvet trays, brass lamps, and sketches cover the desk. Luxury craftsmanship photography, realistic hands, metal reflections, and fine detail.
Bria FIBO 2.0 Text-to-Image generates images from text descriptions with optional reference-image guidance and structured prompting. Choose from a wide range of aspect ratios, generate at 1k or 2k, and control the final framing for creative, commercial, and design workflows.
21 supported framing options.| Parameter | Required | Description |
|---|---|---|
| prompt | Conditional | Text description of the image to generate. Provide at least one of prompt, images, or structured_prompt. |
| structured_prompt | No | Structured generation instructions as a JSON string from a previous generation. Cannot be used together with images. |
| images | No | Up to 1 reference image. Supports JPEG, JPG, PNG, and WEBP. |
| aspect_ratio | No | Output aspect ratio. Supports 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 16:10, 10:16, 2:1, 1:2, 21:9, 9:21, 3:1, 1:3, 4:1, 1:4, 5:1, and 1:5. Default: 1:1. |
| resolution | No | Output resolution tier: 1k or 2k. Default: 1k. Actual dimensions depend on the selected aspect ratio. |
| output_format | No | Output format: png or jpeg. Default: png. |
| seed | No | Optional seed. Omit for random generation. |
structured_prompt.png or jpeg.$0.04 per request.
structured_prompt when continuing or refining a previous structured generation.2k.prompt, images, or structured_prompt.images and structured_prompt cannot be used together.1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, and 16:9.2k uses a different generation pipeline, not FIBO 2, and supports only the standard aspect ratios.1k with either a text prompt (optionally accompanied by one reference image) or structured_prompt alone.prompt with structured_prompt support only the standard aspect ratios.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bria/fibo-2.0/text-to-image with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Fibo 2.0 Text To Image below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "png",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
]
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/bria/fibo-2.0/text-to-image" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/bria/fibo-2.0/text-to-image";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "png",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
]
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "png",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
]
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/bria/fibo-2.0/text-to-image", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout", "deleted"}:
raise RuntimeError(result)
time.sleep(2)Fibo 2.0 Text To Image is a Bria model for image generation, exposed as a REST API on WaveSpeedAI. Bria FIBO 2.0 Text-to-Image creates images from text prompts, with an optional reference image, flexible aspect ratios, and advanced structured prompting for product visuals, marketing assets, creative content, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/bria/bria-fibo-2.0-text-to-image.
Fibo 2.0 Text To Image starts at $0.04 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `images`, `aspect_ratio`, `resolution`, `seed`, `output_format`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/bria/bria-fibo-2.0-text-to-image.
Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.
Commercial usage rights depend on the model's license, set by its provider (Bria). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.