FLUX.1 Kontext Pro
FLUX.1 Kontext Pro is Black Forest Labs's multi-turn image editing model. It is built to preserve character identity, style, and visual consistency across sequential editing steps. It delivers fast inference relative to earlier models in its class.
import { experimental_generateImage as generateImage } from 'ai';
const result = await generateImage({ model: 'bfl/flux-kontext-pro', prompt: 'A red balloon on a wooden table.'});What To Consider When Choosing a Provider
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.
Kontext Pro's iterative editing loop, feeding one output as the next request's input, maps naturally to conversational editing interfaces where users refine an image through a sequence of natural language instructions. Compare $0.04 with other editing tiers.
When to Use FLUX.1 Kontext Pro
Best For
Conversational image editing:
Products where users refine a single image through a sequence of natural language instructions, each building on the previous result
Character consistency pipelines:
Placing a specific person or product across multiple distinct scenes while preserving unique visual attributes
Local editing tasks:
Changing a background, swapping clothing, modifying an expression, or adjusting a single object without disturbing the rest of the frame
Style reference workflows:
Applying the aesthetic of a reference image to a new scene described in text
Consider Alternatives When
Typography and prompt precision:
Kontext Max targets exact prompt adherence and on-image text accuracy beyond Kontext Pro
Masked region inpainting:
FLUX.1 Fill Pro is built for mask-based fill rather than instruction-based editing
Pure text-to-image generation:
FLUX.2 Pro or FLUX.2 Max may be more appropriate when no reference image is needed
Conclusion
FLUX.1 Kontext Pro established iterative, identity-preserving image editing as a practical capability. A human or AI agent can refine an image through many turns without losing the character and style set at the outset. For applications built around conversational or multi-step image editing, Kontext Pro is the foundational model to evaluate.
FAQ
The model accepts the output of one editing step as the reference image for the next. Each turn receives a new instruction and the previous result, preserving identity and style across steps. Black Forest Labs notes that sessions beyond roughly six turns can introduce visual artifacts.
The model extracts and retains distinctive visual features from the reference image (face, clothing, proportions, recognizable attributes) and reapplies them when generating a new scene. A specific character can be placed in an entirely different environment without reconstructing their appearance from scratch.
Yes. Local editing modifies specific elements (an expression, an object, or a piece of text) while leaving surrounding regions unchanged. Global edits transform the entire scene context, moving a subject to a new environment while preserving their visual identity.
Kontext Pro achieves its highest scores on text editing and character preservation within KontextBench's six real-world editing categories, with measurable scores across all six.
Visual artifacts can accumulate. Black Forest Labs documents this limitation with an example showing degradation after six sequential edits. Shorter, more targeted editing sequences avoid this issue.
Yes. You can use Kontext Pro for text-to-image generation without supplying a reference image.
See the pricing section on this page for today's rates. AI Gateway exposes each provider's pricing for FLUX.1 Kontext Pro.
