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Quickstart Guide

Note: For more advanced configurations, see the tutorial and options reference.

Feature Compatibility

For the complete and most accurate feature matrix, refer to the main README.

Model Quickstart Guides

Model Params PEFT LoRA Full-Rank Quantization Mixed Precision Grad Checkpoint Flow Shift TwinFlow LayerSync ControlNet Sliders† Guide
PixArt Sigma 0.6B–0.9B ✗ ✓ int8 optional bf16 ✓ ✗ ✗ ✓ ✓ ✓ SIGMA.md
NVLabs Sana 1.6B–4.8B ✗ ✓ int8 optional bf16 ✓+ ✓ ✓ ✓ ✗ ✓ SANA.md
Kwai Kolors 2.7B ✓ ✓ not recommended bf16 ✓ ✗ ✗ ✗ ✗ ✓ KOLORS.md
Stable Diffusion 3 2B–8B ✓ ✓ int8/fp8/nf4 optional bf16 ✓+ ✓ (SLG) ✓ ✓ ✓ ✓ SD3.md
Flux.1 8B–12B ✓ ✓* int8/fp8/nf4 optional bf16 ✓+ ✓ ✓ ✓ ✓ ✓ FLUX.md
Flux.2 32B ✓ ✓* int8/fp8/nf4 optional bf16 ✓+ ✓ ✓ ✓ ✗ ✓ FLUX2.md
Flux Kontext 8B–12B ✓ ✓* int8/fp8/nf4 optional bf16 ✓+ ✓ ✓ ✓ ✓ ✓ FLUX_KONTEXT.md
Z-Image Turbo 6B ✓ ✓* int8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ ZIMAGE.md
ACE-Step 3.5B ✓ ✓* int8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ ACE_STEP.md
Chroma 1 8.9B ✓ ✓* int8/fp8/nf4 optional bf16 ✓+ ✓ ✓ ✓ ✗ ✓ CHROMA.md
Auraflow 6B ✓ ✓* int8/fp8/nf4 optional bf16 ✓+ ✓ (SLG) ✓ ✓ ✓ ✓ AURAFLOW.md
HiDream I1 17B (8.5B MoE) ✓ ✓* int8/fp8/nf4 optional bf16 ✓ ✓ ✓ ✓ ✓ ✓ HIDREAM.md
OmniGen 3.8B ✓ ✓ int8/fp8 optional bf16 ✓ ✓ ✗ ✗ ✗ ✓ OMNIGEN.md
Stable Diffusion XL 2.6B ✓ ✓ not recommended bf16 ✓ ✗ ✗ ✓ ✓ ✓ SDXL.md
Lumina2 2B ✓ ✓ int8 optional bf16 ✓ ✓ ✓ ✗ ✗ ✓ LUMINA2.md
Cosmos2 2B ✓ ✓ not recommended bf16 ✓ ✓ ✓ ✓ ✗ ✓ COSMOS2IMAGE.md
LTX Video ~2.5B ✓ ✓ int8/fp8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ LTXVIDEO.md
LTX Video 2 19B ✓ ✓* int8/fp8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ LTXVIDEO2.md
Hunyuan Video 1.5 8.3B ✓ ✓* int8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ HUNYUANVIDEO.md
Wan 2.x 1.3B–14B ✓ ✓* int8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ WAN.md
Wan 2.2 S2V 14B ✓ ✓* int8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ WAN_S2V.md
Qwen Image 20B ✓ ✓* required (int8/nf4) bf16 ✓ ✓ ✓ ✓ ✗ ✓ QWEN_IMAGE.md
Qwen Image Edit 20B ✓ ✓* required (int8/nf4) bf16 ✓ ✓ ✓ ✓ ✗ ✓ QWEN_EDIT.md
Stable Cascade (C) 1B, 3.6B prior ✓ ✓* not supported fp32 (required) ✓ ✗ ✗ ✗ ✗ ✓ STABLE_CASCADE_C.md
Kandinsky 5.0 Image 6B (lite) ✓ ✓* int8 optional bf16 ✓ ✓ ✓ ✗ ✗ ✓ KANDINSKY5_IMAGE.md
Kandinsky 5.0 Video 2B (lite), 19B (pro) ✓ ✓* int8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ KANDINSKY5_VIDEO.md
LongCat-Video 13.6B ✓ ✓* int8/fp8 optional bf16 ✓+ ✓ ✓ ✓ ✗ ✓ LONGCAT_VIDEO.md
LongCat-Video Edit 13.6B ✓ ✓* int8/fp8 optional bf16 ✓+ ✓ ✓ ✓ ✗ ✓ LONGCAT_VIDEO_EDIT.md
LongCat-Image 6B ✓ ✓* int8/fp8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ LONGCAT_IMAGE.md
LongCat-Image Edit 6B ✓ ✓* int8/fp8 optional bf16 ✓ ✓ ✓ ✓ ✗ ✓ LONGCAT_EDIT.md

✓ = supported, ✓ = requires DeepSpeed/FSDP2 for full-rank, ✗ = not supported, ✓+ indicates checkpointing is recommended due to VRAM pressure. TwinFlow ✓ means native support when twinflow_enabled=true (diffusion models need diff2flow_enabled+twinflow_allow_diff2flow). LayerSync ✓ means the backbone exposes transformer hidden states for self-alignment; ✗ marks UNet-style backbones without that buffer. †Sliders apply to LoRA and LyCORIS (including full-rank LyCORIS "full"). All models support LyCORIS.*

ℹ️ Wan quickstart includes 2.1 + 2.2 stage presets and the time-embedding toggle. Flux Kontext covers editing workflows built atop Flux.1.

⚠️ These quickstarts are living documents. Expect occasional updates as new models land or training recipes improve.

Fast paths: Z-Image Turbo & Flux Schnell

  • Z-Image Turbo: Fully supported LoRA with TREAD; runs fast on NVIDIA and macOS even without quant (int8 works too). Often the bottleneck is just trainer setup.
  • Flux Schnell: The quickstart config handles the fast noise schedule and assistant LoRA stack automatically; no extra flags needed to train Schnell LoRAs.

Advanced Experimental Features

  • Diff2Flow: Allows training standard epsilon/v-prediction models (SD1.5, SDXL, DeepFloyd, etc.) using a Flow Matching loss objective. This bridges the gap between older architectures and modern flow-based training.
  • Scheduled Sampling: Reduces exposure bias by letting the model generate its own intermediate noisy latents during training ("rollout"). This helps the model learn to recover from its own generation errors.

Common Issues

Dataset has fewer samples than expected

If your dataset ends up with fewer usable samples than you expected, files may have been filtered during processing. Common reasons include:

  • Files too small: Images below minimum_image_size are filtered out
  • Aspect ratio out of range: Images outside minimum_aspect_ratio/maximum_aspect_ratio bounds are excluded
  • Duration limits: Audio/video files exceeding duration limits are skipped

Viewing filtering statistics: - In the WebUI, browse to your dataset directory and select it to see filtering statistics - Check the logs during dataset processing for statistics like: Sample processing statistics: {'total_processed': 100, 'skipped': {'too_small': 15, ...}}

For detailed troubleshooting, see Troubleshooting filtered datasets in the dataloader documentation.