model-compatibility

A reference guide for checking which Stable Diffusion, Flux, Stable Diffusion 3, and video model settings work together in ComfyUI, a visual tool for building AI image workflows. It covers model loaders, image sizes, samplers, text guidance, VAEs, ControlNets, and LoRAs.

In plain words
What is it for?
Choose compatible loaders, resolutions, samplers, guidance settings, VAEs, ControlNets, and LoRAs for supported model families.
Why use it?
Different model families require different components and settings, so incompatible choices can cause errors or poor results. The guide helps identify suitable combinations before building a workflow.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/artokun/comfyui-mcp/model-compatibility
Any agent
npx skills add artokun/comfyui-mcp --skill model-compatibility
Clone the repo
git clone --depth 1 https://github.com/artokun/comfyui-mcp

Made for: Claude Code, Codex.

Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,926 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00047 $0.04926
Opus 5 $0.00023 $0.02463
Sonnet 5 $0.00009 $0.00985
Haiku 4.5 $0.00005 $0.00493

Measured yesterday against content hash 2b3785acb615, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

model-compatibility scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

plugin/skills/model-compatibility/SKILL.md · 441 lines

How it starts

The opening of the file, as written. The whole thing — 441 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ComfyUI Model Compatibility Matrix

Stable Diffusion 1.5 (SD 1.5)

Overview

The original widely-adopted Stable Diffusion model. Huge ecosystem of fine-tunes, LoRAs, ControlNets, and embeddings. Still the most compatible and lightweight model family.

Configuration

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

Workflow Pattern

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 Notes

  • Most SD 1.5 checkpoints have a built-in VAE, but it's often mediocre
  • Recommended: Use external vae-ft-mse-840000-ema-pruned.safetensors for better color accuracy
  • Load via VAELoader node and connect to VAEDecode
  • FP16 VAE can produce NaN on some images. FP32 VAE is more stable

ControlNet Compatibility

SD 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

Read the full file on GitHub · 441 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 441 lines · 47 tokens per session scan A 2b3785acb615

Subscribe to this mod's changes

model-compatibility is a skill published in the GitHub repository artokun/comfyui-mcp (701 stars, last pushed yesterday), licensed MIT. It adds 47 tokens to every session and 4,926 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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