FLUX Kontext [pro] — 12B-param in-context editor. Character consistency, style transfer, local edits. $0.04/image.
In-context image editing and generation — multiple tiers on the same Runflow API.
Premium — best prompt adherence and typography, $0.08/image
Standard — fast in-context editing with character consistency, $0.04/image
Every model on Runflow is scored per vertical — not generic leaderboard numbers. Scores come from domain-expert evaluation on real production prompts.
| Use Case | Assessment | Notes |
|---|---|---|
| Portrait | Strong | Identity-preserving scene changes and lighting edits |
| Fashion | Strong | Outfit and style transfer while maintaining model identity |
| Product | Strong | Context swaps that preserve product detail and branding |
| Creative | Strong | Multi-turn editing with coherent visual style across iterations |
Full parameter reference for the flux-pro-kontext model endpoint.
| Parameter | Type | Description |
|---|---|---|
| prompt | string | Editing instruction describing the desired transformation. |
| image_url | string | URL of the source image to edit. |
| aspect_ratio | string | Output aspect ratio. Options: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9. |
| num_images | integer | Number of images to generate per request. Range: 1–4. Default: 1. |
| guidance_scale | float | How closely the model follows the prompt. Range: 1–20. Default: 3.5. |
| output_format | string | Output format. Options: "jpeg", "png". Default: "jpeg". |
| safety_tolerance | string | Content moderation strictness. 1 = most strict, 6 = most permissive. Default: 2. |
| enhance_prompt | boolean | Automatically enhance the prompt for better results. Default: false. |
| seed | integer | Random seed for reproducible outputs. |
| sync_mode | boolean | Return media as data URI without storing in request history. Default: false. |
Flux AI models are available on many platforms. Here's what makes the Runflow image generation API different.
Preserves subject identity, style, and brand elements across edits — no LoRA training or per-subject fine-tuning needed.
Significantly faster inference than competing in-context editing models while maintaining high-quality results.
Handles everything from targeted region edits (change a shirt colour) to full scene transformations (move from studio to beach) — no separate models or masks needed.
Apply successive refinements that maintain visual coherence — each edit builds on the previous one without degrading quality.
Every output is scored by Runflow's Sentinel system for both generation quality and reference fidelity.
Same API, different strengths. Switch models with one parameter change.
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Get API access in minutes. No GPU setup, no infrastructure to manage. Pair with Sentinel to control the quality of every AI-generated image you ship.