👋 LLaDA-Image combines the LLaDA2.0-mini dLLM understanding backbone with a 6B DiT for high-quality image generation and instruction-guided editing. Both backone and Image-Gen are diffusion models, trained in a unified framework.
🔑 Image-first training at scale:
Of ~220M cumulative generation-training samples, >90% use image-only supervision. Image-text pairs are introduced later for language alignment.
The result is a model family that covers high-quality generation, instruction-guided editing, and fast 2-4-step inference with LLaDA-Image-Turbo.
#OpenSource #inclusionAI #dLLM
alignment — The work of making AI systems actually pursue what their builders and users intend, rather than something subtly or dangerously different.
Why it matters
An open-source stack where both understanding and generation are diffusion, not autoregressive, with a Turbo variant that does instruction-guided editing in 2 to 4 sampling steps.
