Kromoss, a community checkpoint from lodestones, has climbed the Hugging Face trending chart after adding two distilled turbo adapters to OpenMOSS’s 5-billion-parameter image model. The release is a full-parameter fine-tune of MOSS-Image-Base, and its LoRAs reduce the default sampling path from 50 steps to eight.

Developers already using the MOSS-Image code can replace the SFT checkpoint without changing the pipeline architecture. Kromoss retains the same text encoder, VAE, prompt format, JSON layout controls, and ComfyUI graph structure.

A 5B base built for text and layouts

OpenMOSS released MOSS-Image-Base and MOSS-Image-SFT on October 16, 2026. The Apache 2.0 release uses a diffusion transformer, which generates images by repeatedly removing noise under the guidance of a text prompt. It supports prompts of up to 4,000 tokens, English and Chinese text rendering, photorealistic and anime styles, and JSON prompts that specify objects, text, and spatial positions.

Kromoss preserves that architecture and uses the Qwen3.5-9B text encoder with the FLUX.2 small VAE decoder. The 5B label covers the image transformer alone; the complete runtime also loads the 9B text encoder, VAE, and intermediate activations, so total memory requirements exceed the transformer’s parameter footprint.

What the reported score covers

The release reports results from a 100-prompt PartiPrompts evaluation using CLIP ViT-L/14. CLIP scores estimate how closely generated images align with prompt semantics, with higher values indicating stronger measured alignment.