Example workflows
One ready-to-run workflow per model family. Each file is the same three-node graph (Config Builder -> Sampler Grid -> Grid Dashboard) with the Builder already filled in for that model: model, text encoder, CLIP type, VAE, sampler/scheduler/steps/cfg axes and a prompt.
How to load one
- Download the model files listed for the example and put each in the folder shown (under
ComfyUI/models/). The official Comfy-Org workflow templates and Hugging Face repos for each family ship exactly these files.
- Drag the
.json onto the ComfyUI canvas.
- Open the Config Builder. If your file names differ, pick yours in the model / text encoder / VAE dropdowns. A file you do not have is shown as missing rather than silently replaced.
- Queue the prompt. Results appear in the Dashboard node.
Times are approximate on an RTX 5060 Ti 16 GB, not counting the first model load.
SDXL / Illustrious (uscg-sdxl-illustrious.json)
| File |
Folder |
sd_xl_base_1.0.safetensors |
models/checkpoints/ |
- What the grid tests: 2 samplers (dpmpp_2m, euler) x 2 schedulers (karras, normal) x cfg 5 and 7 x 2 prompts at 25 steps, 1024x1024. 16 images
- Time: TBD
- Notes: the checkpoint has the VAE and CLIP built in, so no extra files. Swap in any Illustrious/SDXL checkpoint.
Anima (uscg-anima.json)
| File |
Folder |
anima-base-v1.0.safetensors |
models/diffusion_models/ |
qwen_3_06b_base.safetensors |
models/text_encoders/ |
qwen_image_vae.safetensors |
models/vae/ |
- What the grid tests: 2 samplers (er_sde, euler) x simple scheduler x cfg 4 and 5 at 30 steps, 1024x1024. 4 images
- Time: TBD
- Notes: the CLIP type stays
stable_diffusion; there is no separate Anima option and ComfyUI picks the Anima text encoder from the Qwen3-0.6B file.
Z-Image Turbo (uscg-z-image-turbo.json)
| File |
Folder |
z_image_turbo_bf16.safetensors |
models/diffusion_models/ |
qwen_3_4b.safetensors |
models/text_encoders/ |
ae.safetensors |
models/vae/ |
- What the grid tests: res_multistep / simple at 8 and 10 steps, cfg 1, 1024x1024. 2 images
- Time: TBD
- Notes: CLIP type
lumina2. Model Sampling is set to AuraFlow with shift 3, as in the official template.
Krea 2 Turbo (uscg-krea2-turbo.json)
| File |
Folder |
krea2_turbo_fp8_scaled.safetensors |
models/diffusion_models/ |
qwen3vl_4b_fp8_scaled.safetensors |
models/text_encoders/ |
qwen_image_vae.safetensors |
models/vae/ |
- What the grid tests: euler / simple at 6 and 8 steps, cfg 1, 1024x1024. 2 images
- Time: TBD
- Notes: CLIP type
krea2.
Flux.2 Klein 9B (uscg-flux2-klein-9b.json)
| File |
Folder |
flux-2-klein-9b-fp8.safetensors |
models/diffusion_models/ |
qwen_3_8b_fp8mixed.safetensors |
models/text_encoders/ |
flux2-vae.safetensors |
models/vae/ |
- What the grid tests: euler at 4 and 6 steps, 1024x1024, each with the Advanced Sampling pipeline (CFG guider + Flux2 scheduler) and without it (plain KSampler, simple scheduler): the Builder always grids Advanced Sampling on vs off. 4 images
- Time: TBD
- Notes: Klein is distilled, so cfg is 1; the official template uses the CFG guider plus the Flux2 scheduler, which is the Advanced Sampling half of the grid. CLIP type
flux2.
MOSS-Image (uscg-moss-image.json)
| File |
Folder |
moss_image_sft_int8_convrot.safetensors |
models/diffusion_models/ |
qwen3.5_9b_w4a8_gptq.safetensors |
models/text_encoders/ |
flux2-vae.safetensors |
models/vae/ |
- What the grid tests: two config arrays with the same prompt and settings (er_sde / simple, 25 steps, cfg 2.5): one with Skip Layer Guidance on, one off. 2 images
- Time: TBD
- Notes: SLG uses the official recipe, single block 22 for the first 0-50 % of the steps. Compare the two images to see what it does. CLIP type
moss_image. A smaller flux2-vae_small.safetensors VAE also exists and can be picked in the Builder instead. The 9B text encoder is large; on a 16 GB card expect model swapping.
Make your own
- Edit the Builder: add LoRAs or a whole LoRA folder, more samplers, schedulers, step counts, cfg values, resolutions or prompts. Every list is multiplied together.
- Raise Additional Random Seeds in Run Settings to render extra seeds per config, handy for telling what the model does from what a LoRA does.
- Add another config array to compare models or settings side by side (the MOSS example does this for SLG).
