Local Ai
MOSS-Image (5B, Apache 2.0) on a 12 GB RTX 3060: INT8 quant + lodestones' 8-step DMD turbo in ComfyUI - 35 hard prompts, one seed, no cherry-picking
Tested the new MOSS-Image (5B single-stream DiT, Qwen3.5-9B text encoder, FLUX.2 VAE, Apache 2.0) on a plain RTX 3060 12 GB / 16 GB RAM with 35 deliberately hard prompts: dense on-image text in Englis
Tested the new MOSS-Image (5B single-stream DiT, Qwen3.5-9B text encoder, FLUX.2 VAE, Apache 2.0) on a plain RTX 3060 12 GB / 16 GB RAM with 35 deliberately hard prompts: dense on-image text in English/Chinese/Japanese, accents, exact counts, attribute binding, spatial relations, negation, hands, clocks, very long prompts, and MOSS's Layout JSON. One seed (42), first result, no cherry-picking, failures included. The first image is a contact sheet of all 35. Setup Model: u/XCEED123's INT8 ConvRot quant (HF), ~15 GB total, with the official ComfyUI node (comfyui/moss-image from the GitHub repo). Peaks at ~9.7 GB VRAM. Base: 50 steps, euler / sgm_uniform, CFG 3, shift 5, uncond layer-skip 22. 137 s at 1 MP, ~230 s at 1.6 MP, 340 s at 2.1 MP. Turbo: lodestones' 8-step DMD (still training). It isn't a normal LoRA: the card says the delta is smaller than bf16 rounding, so it has to run unmerged in fp32 along with fp32 time-embedding/modulation biases and its own data-space sampler (no CFG, no scheduler). I wrote a small ComfyUI node that does this on top of the INT8 base model. ~24 s at 1 MP, ~36 s at 1.6 MP, about 6× faster. What I saw Text rendering is very strong: menus, letters, labels with accents, Chinese chalkboards, Japanese signage, and bilingual neon all came out with almost no mistakes, even on turbo. Layout JSON works: posters, a 4-panel comic and an infographic follow the boxes. Long prompts hold up remarkably well (the ~300-word market scene). Turbo is close to base on text and layout, but drifts more on lighting ("chiaroscuro" came out evenly lit) and fine constraints (clock times, a chess position, fish-eye). Short prompts look generic because it has no CFG. Both still fail negation ("no cars") and specific clock times (it draws 10:10). Links All 35 prompts (incl. the Layout JSON), sizes and settings: https://pastebin.com/U8nChbZ9 Turbo node + ComfyUI workflow: https://pastebin.com/9trM12Qc Base workflow: in XCEED123's HF repo (workflows/) Credits: OpenMOSS for the model, XCEED123 for the quant, lodestones for the DMD distillation. submitted by /u/mearbode [link] [comments]
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Source: r/StableDiffusion | 2026-10-16