FLUX.1 Kontext

SeedEdit is an advanced AI image-editing model developed by the ByteDance Seed team that enables users to revise an existing image using natural-language text prompts while preserving unedited regions with high fidelity. It accepts an input image plus a text description of the change (such as style conversion, object removal or replacement, background swap, lighting shift, or text change), and produces a seamlessly edited result that maintains structural integrity, resolution, and identity of the original content. The model leverages a diffusion-based architecture trained via a meta-information embedding pipeline and joint loss (combining diffusion and reward losses) to balance image reconstruction and re-generation, resulting in strong editing controllability, detail retention, and prompt adherence. The latest version (SeedEdit 3.0) supports high-resolution edits (up to 4 K), delivers fast inference (under ~10-15 seconds in many cases), and handles multi-round sequential edits.

FLUX.1 Krea is an open source, guidance-distilled 12 billion-parameter diffusion transformer released by Krea in collaboration with Black Forest Labs, engineered to deliver superior aesthetic control and photorealism while eschewing the generic “AI look.” Fully compatible with the FLUX.1-dev ecosystem, it starts from a raw, untainted base model (flux-dev-raw) rich in world knowledge and employs a two-phase post-training pipeline, supervised fine-tuning on a hand-curated mix of high-quality and synthetic samples, followed by reinforcement learning from human feedback using opinionated preference data, to bias outputs toward a distinct style. By leveraging negative prompts during pre-training, custom loss functions for classifier-free guidance, and targeted preference labels, it achieves significant quality improvements with under one million examples, all without extensive prompting or additional LoRA modules.