FLUX.2 [flex]
FLUX.2 [flex] is Black Forest Labs's developer-tunable image generation model. It exposes direct control over inference steps and guidance scale, letting you trade typography accuracy and fine detail against generation speed within a single model.
import { experimental_generateImage as generateImage } from 'ai';
const result = await generateImage({ model: 'bfl/flux-2-flex', prompt: 'A red balloon on a wooden table.'});Playground
Try out FLUX.2 [flex] by Black Forest Labs. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.
FLUX.2 [flex]
Your generated image will appear here
Providers
Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.
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About FLUX.2 [flex]
FLUX.2 [flex] belongs to the FLUX.2 family from Black Forest Labs. Other FLUX.2 variants optimize for a fixed quality level. Flex gives you direct control over the number of inference steps and the guidance scale.
The FLUX.2 architecture pairs a Mistral-3 24B vision-language model (VLM) with a rectified flow transformer retrained on a new variational autoencoder (VAE). The VLM contributes real-world knowledge and contextual understanding, producing more coherent scenes, correct spatial logic, and reliable typography. FLUX.2 supports multi-reference input with up to 10 reference images and image editing at resolutions up to 4 megapixels.
Flex's role in the lineup is explicit parameter control. If you build workflows that span multiple quality tiers (a quick draft view and a high-fidelity export, for example), you can use one Flex endpoint and change the steps value instead of switching models. That makes Flex a natural fit for tools, pipelines, and interfaces that expose a quality dial to end users.
What To Consider When Choosing a Provider
- Configuration: Because FLUX.2 [flex] exposes the
stepsparameter, you can run a quick low-step pass to validate a composition before you commit to a full-quality render. That cuts iteration cost during prompt development. Compare N/A against other FLUX.2 tiers. - Zero Data Retention: AI Gateway does not currently support Zero Data Retention for this model. See the documentation for models that support ZDR.
- Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.
When to Use FLUX.2 [flex]
Best for
- Configurable quality-speed tradeoff: Single model that supports draft previews at six steps and final renders at 50 steps
- Typography accuracy: Applications like UI mockup generation or infographic creation where fine text legibility matters
- Iterative prompt development: Rapid low-step passes validate composition before committing to full-quality generation
- Quality slider interfaces: Developer tools that expose a quality control mapped to inference step count
Consider alternatives when
- Maximum automatic quality: FLUX.2 Pro handles this with tuned default parameters when you don't want to manage inference parameters
- Image inpainting: FLUX.1 Fill Pro is purpose-built for masked region fill tasks
- Real-time generation: FLUX.2 Klein is optimized for sub-second interactive speed
Conclusion
FLUX.2 [flex] gives you direct control over inference steps and guidance scale. Choose it when your application needs to tune the quality-speed tradeoff at runtime rather than commit to a fixed output tier. Its strength in text rendering and fine detail makes it especially useful for structured visual content like UI mockups and infographics.