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Bria FIBO is an advanced text-to-image generation model designed for professional-grade visual content creation. Unlike conventional image generators, FIBO uses a Vision-Language Model (VLM) bridge to transform natural language prompts and reference images into structured JSON instructions, enabling unprecedented control over output quality and style. This architecture separates intent understanding from image synthesis, allowing developers to inspect, modify, and fine-tune generation parameters before rendering. FIBO excels at producing high-fidelity, commercially viable images with scalable resolutions and customizable workflows, making it ideal for enterprise applications requiring consistent brand aesthetics and legal compliance.
FIBO shines in scenarios requiring precise control and professional output quality:
Effective FIBO prompts balance specificity with flexibility:
Text Prompts: Use detailed, descriptive language. Instead of "city," write "A futuristic city skyline at night with neon lights reflecting off rain-soaked streets." Include lighting conditions, atmosphere, and mood.
Structured Prompts: Leverage the JSON format to define precise styles. For example: {"style": "cyberpunk", "lighting": "dramatic", "color_palette": "neon_blue_and_purple"} gives you granular control over aesthetic elements.
Reference Images: Provide high-quality reference URLs when you need stylistic consistency. The VLM will analyze composition, color schemes, and visual patterns to guide generation.
Seed Usage: Set a specific seed value when iterating designs or creating variations. This ensures reproducibility across API calls, crucial for A/B testing and refinement workflows.
Content Moderation: Keep prompt and visual content moderation enabled for production environments to maintain brand safety and comply with content policies.
Is Bria FIBO open-source?
The core FIBO model is proprietary, but Bria is developing an open-source FIBO-VLM option for on-premises deployment, providing flexibility for organizations with strict data governance requirements.
How is FIBO different from other text-to-image models?
FIBO's structured prompt architecture separates intent understanding from image generation, allowing developers to inspect and modify the intermediate JSON representation. This provides unprecedented control compared to black-box models like Stable Diffusion or DALL-E.
What parameters should I tweak for best results?
Start with detailed text prompts and reference images. Use structured JSON prompts for fine-grained style control. Adjust the seed parameter when you need reproducible variations, and enable content moderation for production environments.
Can I use generated images commercially?
Bria FIBO is designed for commercial use with built-in IP conflict detection. However, review your specific licensing agreement and use the IP signal feature to identify potential conflicts.
What image formats and resolutions are supported?
FIBO supports scalable resolution generation. Reference images should be provided as accessible URLs in common formats (JPEG, PNG). Output quality scales with model parameters.
How does content moderation work?
FIBO includes optional prompt and visual input moderation that flags inappropriate content before generation. This helps maintain brand safety and comply with content policies across automated workflows.