FLUX.2, developed by Black Forest Labs, is an advanced image generation model that builds upon its predecessor, Flux.1, with a new architecture designed from the ground up. Unlike Flux.1, FLUX.2 employs a single text encoder, Mistral Small 3.1, simplifying prompt embedding by stacking outputs from intermediate layers. The model retains the multimodal diffusion transformer (MM-DiT) + parallel DiT architecture but introduces modifications such as shared modulation parameters across transformer blocks and the elimination of bias parameters, leading to a more streamlined structure. FLUX.2 supports both image-guided and text-guided generation, allows multiple reference images, and provides advanced prompting techniques. It requires significant memory resources, with various strategies available to optimize inference and fine-tuning on consumer-grade hardware. Users can leverage techniques like LoRA fine-tuning, remote text encoding, and quantization to maximize efficiency and performance, making FLUX.2 a versatile tool for complex image generation tasks.