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bria/fibo-2.0/text-to-image

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.

Text to Image
Input

Advanced generation instructions as a JSON string from a previous generation. Do not combine with images. Combining with prompt supports only the nine standard aspect ratios.

Idle

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.

$0.04per run·~25 / $1

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ExamplesView all

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.

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.

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.

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.

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.

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.

Related Models

README

Bria FIBO 2.0 Text-to-Image

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.

Why Choose This?

  • Text-to-image generation — Create images from detailed descriptions of the subject, setting, style, and composition.
  • Reference-guided generation — Use one image to guide the visual direction.
  • Structured prompting — Reuse structured generation instructions from previous results.
  • Flexible aspect ratios — Choose from 21 supported framing options.
  • 1K and 2K output — Select the resolution tier that fits your workflow.
  • PNG and JPEG output — Choose the preferred image format.

Parameters

ParameterRequiredDescription
promptConditionalText description of the image to generate. Provide at least one of prompt, images, or structured_prompt.
structured_promptNoStructured generation instructions as a JSON string from a previous generation. Cannot be used together with images.
imagesNoUp to 1 reference image. Supports JPEG, JPG, PNG, and WEBP.
aspect_ratioNoOutput 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.
resolutionNoOutput resolution tier: 1k or 2k. Default: 1k. Actual dimensions depend on the selected aspect ratio.
output_formatNoOutput format: png or jpeg. Default: png.
seedNoOptional seed. Omit for random generation.

How to Use

  1. Describe the image — Write a prompt describing the subject, composition, lighting, and visual style.
  2. Add guidance optional — Supply one reference image or reuse a structured_prompt.
  3. Choose framing — Select an aspect ratio and resolution.
  4. Choose output format optional — Select png or jpeg.
  5. Set a seed optional — Use a fixed seed when reproducibility is useful.
  6. Submit — Generate and retrieve the finished image.

Pricing

$0.04 per request.

Best Use Cases

  • Advertising creatives — Generate campaign and promotional visuals.
  • Product concepts — Explore product presentation and commercial imagery.
  • Editorial content — Create images for publishing, social media, and marketing.
  • Reference-guided creation — Use an existing image to influence the visual direction.
  • Structured workflows — Reuse structured generation instructions across iterations.
  • Custom-format graphics — Generate images across a wide range of aspect ratios.

Pro Tips

  • Describe the subject, environment, lighting, composition, and style clearly.
  • Use a reference image when visual consistency is important.
  • Use structured_prompt when continuing or refining a previous structured generation.
  • Choose a standard aspect ratio when using 2k.
  • Use a fixed seed when comparing prompt or parameter changes.

Notes

  • Provide at least one of prompt, images, or structured_prompt.
  • images and structured_prompt cannot be used together.
  • Standard aspect ratios are 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.
  • Extended aspect ratios require 1k with either a text prompt (optionally accompanied by one reference image) or structured_prompt alone.
  • Reference-only requests and requests combining prompt with structured_prompt support only the standard aspect ratios.
  • Resolution tiers are square-equivalent, not fixed output dimensions. Actual width and height vary with the selected aspect ratio.
  • For structured prompting, reuse the complete structured JSON from a previous generation.

Related Models

Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Fibo 2.0 Text To Image API — Quick start

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.

HTTP example
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
done
Node.js example
const 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));
}
Python example
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 API — Frequently asked questions

What is the Fibo 2.0 Text To Image API?

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.

How do I call the Fibo 2.0 Text To Image API?

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.

How much does Fibo 2.0 Text To Image cost per run?

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.

What inputs does Fibo 2.0 Text To Image accept?

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.

How do I get started with the Fibo 2.0 Text To Image API?

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.

Can I use Fibo 2.0 Text To Image outputs commercially?

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.

llms.txt — bria/fibo-2.0/text-to-image for AI agents and LLMs