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Model family compatibility matrix — loaders, resolutions, samplers, CFG, VAE, ControlNet, and LoRA compatibility for SD 1.5, SDXL, Flux, SD3, and video models
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Drive the LTX Director (Timeline) node — its Add Image/Text/Audio buttons are DOM-only and cannot be clicked by an agent; edit the hidden timeline_data JSON widget instead. Load when a workflow contains LTXDirector / LTXDirectorGuide / PromptRelayEncodeTimeline, or when asked to add, move, retime, or remove timeline segments (image / text / audio / motion).
Train a character/identity LoRA locally on FLUX.1-dev via the comfyui-mcp train_* tools (GPU Docker + ostris ai-toolkit). Use when the user wants to train a LoRA of a person/character from their photos on the local GPU — covers dataset prep, launch, monitoring, and using the result in ComfyUI. For WAN/Z-Image training via the ai-toolkit UI see ai-toolkit-trainer.
Core ComfyUI knowledge — workflow format, node types, pipeline patterns, and MCP tool usage
Discover Civitai models with the BUILT-IN search_civitai_models tool and install/generate them locally — find a checkpoint/LoRA/embedding on Civitai, download it into ComfyUI, and use its trigger words. Optionally pair the official Civitai MCP for community features (images browsing, posting, collections).
Run the ComfyUI agent locally for FREE — no subscription, no API key, fully offline — using our gemma4 models fine-tuned on the comfyui-mcp tool suite via Ollama. Use when the user asks about running locally, running for free, offline use, avoiding API costs, Ollama setup, or which local model to pick.
Debug a WRONG or imperfect render (not a hard error) by inspecting inputs and intermediate steps with run-to-node — render one branch up to an output, preview-tap latents/masks/preprocessor maps, localize the first bad stage, then fix. Use when a final image/video comes out wrong — artifacts, wrong subject/pose/composition/color, blur, a ControlNet/IPAdapter/mask/LoRA not taking, a two-stage refiner or upscale degrading the result — rather than the run failing with an error (for errors/OOM/missing nodes use the troubleshooting skill).
| name | model-compatibility |
| description | Model family compatibility matrix — loaders, resolutions, samplers, CFG, VAE, ControlNet, and LoRA compatibility for SD 1.5, SDXL, Flux, SD3, and video models |
| globs | ["**/*.json"] |
The original widely-adopted Stable Diffusion model. Huge ecosystem of fine-tunes, LoRAs, ControlNets, and embeddings. Still the most compatible and lightweight model family.
| Parameter | Value |
|---|---|
| Loader | CheckpointLoaderSimple |
| Native Resolution | 512x512 |
| Supported Resolutions | 512x512, 512x768, 768x512, 768x768 (some fine-tunes) |
| VAE | Built-in or external (vae-ft-mse-840000-ema-pruned.safetensors) |
| CLIP | Single CLIP-L (output index 1 from checkpoint) |
| Text Encoder Node | CLIPTextEncode |
| CFG Range | 7-12 (typical: 7.5) |
| Negative Prompt | Yes — very important for quality |
| Steps | 20-30 (standard samplers) |
| Sampler | All standard samplers: euler, euler_ancestral, dpmpp_2m, dpmpp_sde, ddim |
| Scheduler | normal, karras |
| Denoise | 1.0 (txt2img), 0.5-0.8 (img2img) |
| VRAM (FP16) | ~2-3GB |
CheckpointLoaderSimple → MODEL(0), CLIP(1), VAE(2)
CLIP(1) → CLIPTextEncode (positive) → CONDITIONING
CLIP(1) → CLIPTextEncode (negative) → CONDITIONING
EmptyLatentImage (width=512, height=512) → LATENT
KSampler (cfg=7.5, steps=20, sampler="euler", scheduler="normal") → LATENT
VAEDecode → IMAGE
SaveImage
vae-ft-mse-840000-ema-pruned.safetensors for better color accuracyVAELoader node and connect to VAEDecodeSD 1.5 has the largest ControlNet ecosystem:
| ControlNet | Model File Pattern | Notes |
|---|---|---|
| Canny | control_v11p_sd15_canny | Edge detection |
| Depth | control_v11f1p_sd15_depth | Depth map |
| OpenPose | control_v11p_sd15_openpose | Skeleton/pose |
| Scribble | control_v11p_sd15_scribble | Hand-drawn lines |
| Lineart | control_v11p_sd15_lineart | Clean lines |
| Softedge | control_v11p_sd15_softedge | Soft edges (HED) |
| Normal | control_v11p_sd15_normalbae | Normal maps |
| Seg | control_v11p_sd15_seg | Semantic segmentation |
| Tile | control_v11f1e_sd15_tile | Tile/upscale guidance |
| Inpaint | control_v11p_sd15_inpaint | Inpainting guidance |
| IP-Adapter | ip-adapter_sd15 | Image prompt |
.safetensors in models/loras/LoraLoader node — connects between checkpoint and CLIPTextEncodeMajor upgrade from SD 1.5 with dual CLIP encoders, higher native resolution, and better prompt understanding. Includes Turbo and Lightning variants for fast generation.
| Parameter | Value |
|---|---|
| Loader | CheckpointLoaderSimple |
| Native Resolution | 1024x1024 |
| Supported Resolutions | 1024x1024, 832x1216, 1216x832, 896x1152, 1152x896, 768x1344, 1344x768 |
| VAE | Built-in (SDXL has good integrated VAE) |
| CLIP | Dual CLIP: CLIP-L + CLIP-G |
| Text Encoder Node | CLIPTextEncode (unified) or CLIPTextEncodeSDXL (separate G/L) |
| CFG Range | 5-10 (typical: 7.0) |
| Negative Prompt | Yes — moderately important |
| Steps | 20-40 |
| Sampler | euler, euler_ancestral, dpmpp_2m, dpmpp_sde |
| Scheduler | normal, karras |
| Denoise | 1.0 (txt2img), 0.5-0.8 (img2img) |
| VRAM (FP16) | ~6-7GB |
| Parameter | Value |
|---|---|
| Loader | CheckpointLoaderSimple |
| Resolution | 512x512 (optimized for lower res) |
| CFG | 1.0-2.0 |
| Steps | 1-4 |
| Sampler | euler_ancestral |
| Scheduler | normal |
| Negative Prompt | Minimal or empty |
| Denoise | 1.0 |
| Parameter | Value |
|---|---|
| Loader | CheckpointLoaderSimple + LoraLoader (Lightning LoRA) |
| Resolution | 1024x1024 |
| CFG | 1.0-2.0 |
| Steps | 4-8 (match the Lightning variant: 2-step, 4-step, 8-step) |
| Sampler | euler |
| Scheduler | sgm_uniform |
| Negative Prompt | Empty or minimal |
| Special | Requires matching Lightning LoRA for the step count |
The optional SDXL refiner model does a second pass to improve fine details:
CheckpointLoaderSimple (base) → KSampler (steps=25, start=0, end=20)
CheckpointLoaderSimple (refiner) → KSampler (steps=25, start=20, end=25)
KSamplerAdvanced with start_at_step and end_at_stepsd_xl_refiner_1.0.safetensorsCheckpointLoaderSimple → MODEL(0), CLIP(1), VAE(2)
CLIP(1) → CLIPTextEncode (positive) → CONDITIONING
CLIP(1) → CLIPTextEncode (negative) → CONDITIONING
EmptyLatentImage (width=1024, height=1024) → LATENT
KSampler (cfg=7.0, steps=25, sampler="dpmpp_2m", scheduler="karras") → LATENT
VAEDecode → IMAGE
SaveImage
SDXL ControlNets are separate from SD 1.5 ControlNets:
| ControlNet | Model File Pattern | Notes |
|---|---|---|
| Canny | control-lora-canny-rank256 or diffusers_xl_canny | Often LoRA-based |
| Depth | control-lora-depth-rank256 or diffusers_xl_depth | |
| T2I-Adapter | t2i-adapter-*-sdxl | Lighter alternative to ControlNet |
| IP-Adapter | ip-adapter_sdxl | Image prompt adapter |
| InstantID | instantid-* | Face-specific |
LoraLoader node as SD 1.5Black Forest Labs' model with a T5-XXL text encoder. Produces high-quality images without negative prompts. Available in schnell (fast) and dev (quality) variants.
| Parameter | Value |
|---|---|
| Loader | CheckpointLoaderSimple (single-file) or DualCLIPLoader + UNETLoader + VAELoader (split) |
| Native Resolution | 1024x1024 (flexible aspect ratios) |
| Supported Resolutions | Flexible: 512x512 to 2048x2048, any aspect ratio |
| VAE | Separate Flux VAE (ae.safetensors) — NOT shared with SD models |
| CLIP | T5-XXL + CLIP-L via DualCLIPLoader |
| Text Encoder Node | CLIPTextEncode (single combined) |
| CFG | 1.0 (MUST be 1.0 — higher values cause severe artifacts) |
| Negative Prompt | NONE — do not connect negative conditioning |
| Steps | 4 |
| Sampler | euler |
| Scheduler | simple or sgm_uniform |
| Denoise | 1.0 |
| VRAM (FP16) | ~24GB (FP8: ~12GB) |
| Parameter | Value |
|---|---|
| Same as Schnell except: | |
| Steps | 20-50 (typical: 30) |
| Scheduler | sgm_uniform |
| VRAM (FP16) | ~24GB (FP8: ~12GB) |
Method 1: Single Checkpoint (simplest)
CheckpointLoaderSimple (ckpt_name="flux1-schnell.safetensors")
→ MODEL(0), CLIP(1), VAE(2)
Method 2: Split Components (recommended for FP8)
UNETLoader (unet_name="flux1-schnell-fp8.safetensors") → MODEL
DualCLIPLoader (clip_name1="t5xxl_fp16.safetensors", clip_name2="clip_l.safetensors", type="flux") → CLIP
VAELoader (vae_name="ae.safetensors") → VAE
ae.safetensors), not SD VAEsUNETLoader (flux fp8) → MODEL
DualCLIPLoader (t5xxl + clip_l, type="flux") → CLIP
VAELoader (ae.safetensors) → VAE
CLIPTextEncode (positive prompt) → CONDITIONING
(no negative CLIPTextEncode needed)
EmptyLatentImage (width=1024, height=1024) → LATENT
KSampler (cfg=1.0, steps=4, sampler="euler", scheduler="simple") → LATENT
VAEDecode (vae from VAELoader) → IMAGE
SaveImage
Flux ControlNets are model-specific:
| ControlNet | Notes |
|---|---|
| Flux ControlNet (Canny) | Specific Flux-compatible ControlNet |
| Flux ControlNet (Depth) | Specific Flux-compatible ControlNet |
| InstantX ControlNets | Community Flux ControlNets |
| Flux IP-Adapter | Image prompt for Flux |
SD 1.5 and SDXL ControlNets do NOT work with Flux.
LoraLoader same as SD modelsStability AI's next-generation model with triple CLIP architecture. Better prompt adherence and longer prompt support via T5-XXL.
| Parameter | Value |
|---|---|
| Loader | CheckpointLoaderSimple or triple-clip loader |
| Native Resolution | 1024x1024 |
| VAE | Built-in (integrated) |
| CLIP | Triple: CLIP-L + CLIP-G + T5-XXL |
| Text Encoder Node | CLIPTextEncode or CLIPTextEncodeSD3 |
| CFG Range | 4-7 (typical: 5.0) |
| Negative Prompt | Minimal — SD3 needs very little negative guidance |
| Steps | 20-30 |
| Sampler | euler, dpmpp_2m |
| Scheduler | sgm_uniform, normal |
| Denoise | 1.0 (txt2img) |
| Shift | Some samplers support a shift parameter for SD3 |
| VRAM (FP16) | ~12GB (without T5-XXL: ~6GB) |
CheckpointLoaderSimple → MODEL(0), CLIP(1), VAE(2)
Or for separate CLIP control:
DualCLIPLoader (clip_l + clip_g) → CLIP
CLIPLoader (t5xxl) → CLIP
shift parameter in sampling affects noise scheduleLatent video diffusion models for text-to-video and image-to-video generation. Very VRAM-intensive.
| Parameter | Value |
|---|---|
| Loader | Special video checkpoint loader (varies by node pack) |
| Resolution | 512x512 or 768x768 per frame (depends on model) |
| Frames | 16-64 (depends on VRAM) |
| FPS | 8-24 |
| VRAM | 20GB+ FP16, ~6-10GB FP8 |
| Key Warning | Can OOM on 24GB VRAM — always use FP8 quantized models |
--lowvram flag for ComfyUILoRAs are model-family specific and are NOT interchangeable:
| LoRA Trained For | Works With | Does NOT Work With |
|---|---|---|
| SD 1.5 | SD 1.5 and its fine-tunes | SDXL, Flux, SD3 |
| SDXL | SDXL and its fine-tunes | SD 1.5, Flux, SD3 |
| Flux | Flux models only | SD 1.5, SDXL, SD3 |
| SD3 | SD3/3.5 models only | SD 1.5, SDXL, Flux |
Using a LoRA with the wrong base model will produce garbage images or errors.
ControlNets are also model-family specific:
| ControlNet Trained For | Works With | Does NOT Work With |
|---|---|---|
| SD 1.5 (v1.1 series) | SD 1.5 base + fine-tunes | SDXL, Flux, SD3 |
| SDXL | SDXL base + fine-tunes | SD 1.5, Flux, SD3 |
| Flux | Flux models only | SD 1.5, SDXL, SD3 |
| VAE | Compatible Models | Notes |
|---|---|---|
vae-ft-mse-840000-ema-pruned | SD 1.5 family | Best external VAE for SD 1.5 |
| SDXL built-in VAE | SDXL family | Good quality, no external needed |
sdxl_vae.safetensors | SDXL family | External SDXL VAE option |
ae.safetensors (Flux VAE) | Flux only | Required for Flux, incompatible with SD |
| SD3 built-in VAE | SD3 family | Integrated, no external needed |
Rule: Never mix VAEs across model families. An SD 1.5 VAE decoding Flux latents will produce garbage.
| Embedding Type | Compatible Models |
|---|---|
| SD 1.5 embeddings | SD 1.5 family only |
| SDXL embeddings | SDXL family only |
| Flux/SD3 | Generally don't use traditional embeddings |
Most samplers work across all models, but some combinations are optimal:
| Model | Best Sampler | Best Scheduler | Notes |
|---|---|---|---|
| SD 1.5 | euler_ancestral, dpmpp_2m | karras, normal | All standard samplers work |
| SDXL | dpmpp_2m, euler | karras, normal | Same as SD 1.5 |
| SDXL Turbo | euler_ancestral | normal | Must use 1-4 steps |
| SDXL Lightning | euler | sgm_uniform | Must match step count to LoRA |
| Flux Schnell | euler | simple | 4 steps only |
| Flux Dev | euler | sgm_uniform | 20-50 steps |
| SD3 | euler, dpmpp_2m | sgm_uniform, normal | Lower CFG needed |
| Use Case | Recommended Model | Why |
|---|---|---|
| Maximum ecosystem/community support | SD 1.5 | Most LoRAs, ControlNets, embeddings |
| High quality, good prompt following | SDXL | Best balance of quality and ecosystem |
| Fastest generation | SDXL Turbo/Lightning | 1-4 steps |
| Best prompt understanding | Flux Dev | T5-XXL encoder, natural language |
| Fast + good quality | Flux Schnell | 4 steps, no negative needed |
| Text in images | SD3.5 | Best text rendering |
| Low VRAM (<6GB) | SD 1.5 | Smallest memory footprint |
| Video generation | LTXV / AnimateDiff | Only options for video |
| Model | Minimum | Recommended | Maximum (before OOM on 24GB) |
|---|---|---|---|
| SD 1.5 | 256x256 | 512x512 | 768x768 |
| SDXL | 512x512 | 1024x1024 | 1536x1536 |
| Flux (FP8) | 512x512 | 1024x1024 | 2048x2048 |
| Flux (FP16) | 512x512 | 1024x1024 | 1024x1024 (tight) |
| SD3 | 512x512 | 1024x1024 | 1536x1536 |
Going below the recommended resolution produces blurry/low-quality results. Going above the maximum risks OOM errors or quality degradation (tiling artifacts).