AuraFlow Text to Image
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AuraFlow v0.3 | [text-to-image]
AuraFlow v0.3 delivers state-of-the-art GenEval results through flow-based diffusion architecture. This open-source model trades raw speed for semantic precision, requiring 50 inference steps at 1024x1024 resolution with optional prompt expansion that enhances natural language interpretation. Built for developers who need production-grade image generation without licensing constraints or API rate limits.
Use Cases: Marketing asset generation | Product visualization | Creative prototyping
Performance
AuraFlow positions as a quality-first alternative in the open-source text-to-image space, achieving top-tier GenEval scores while maintaining cost efficiency through fal's infrastructure.
| Metric | Result | Context |
|---|---|---|
| GenEval Score | State-of-the-art | Top performance on compositional generation benchmark |
| Inference Speed | ~50 steps default | Configurable 20-50 steps for speed/quality tradeoff |
| Output Resolution | 1024x1024 | Fixed resolution optimized for quality consistency |
| License | Open-source | Commercial use permitted, full model weights available |
What Flow-Based Architecture Delivers
AuraFlow uses flow matching instead of traditional diffusion noise scheduling, learning direct mappings from noise to image rather than iterative denoising steps. This architectural choice prioritizes semantic coherence over generation speed, particularly for complex multi-object compositions that trip up standard diffusion models.
What this means for you:
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Prompt expansion by default: Built-in natural language enhancement transforms simple descriptions into detailed generation parameters, reducing prompt engineering overhead
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Configurable inference budget: 20-50 step range lets you trade quality for speed, use 20 steps for rapid iteration, 50 for final assets
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Batch generation support: Generate up to 2 images per request with consistent seed control for variation testing
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Deterministic outputs: Seed parameter ensures reproducible results across API calls for version control and A/B testing
Technical Specifications
| Spec | Details |
|---|---|
| Architecture | AuraFlow v0.3 |
| Input Formats | Text prompts (string) with optional guidance scale (0-20) |
| Output Formats | PNG images (1024x1024), URL-based delivery via CDN |
| Inference Steps | 20-50 configurable steps (default: 50) |
| License | Open-source, commercial use permitted |
API Documentation | Quickstart Guide | Enterprise Pricing
How It Stacks Up
FLUX.1 [dev] – AuraFlow prioritizes GenEval compositional accuracy through flow-based architecture for multi-object scenes. FLUX.1 [dev] emphasizes resolution flexibility and fine detail control for precision visual work where exact layout matters more than semantic interpretation.
Stable Diffusion 3 – AuraFlow trades inference speed (50 steps typical) for semantic coherence on complex prompts. Stability AI's SD3 achieves faster generation but requires more careful prompt engineering for multi-subject compositions where AuraFlow's prompt expansion excels.