Text-to-Image
GGUF
English
wan 2.2
text to image
upscale
inpainting
controlnet
depth
canny
redux
comfyui
flux
krea
sdxl
kontext
nunchuka
Instructions to use MaxedOut/ComfyUI-Starter-Packs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use MaxedOut/ComfyUI-Starter-Packs with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="MaxedOut/ComfyUI-Starter-Packs", filename="Flux1/clip/GGUF/t5xxl_Q5_K_M.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use MaxedOut/ComfyUI-Starter-Packs with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf MaxedOut/ComfyUI-Starter-Packs:Q4_K_M # Run inference directly in the terminal: llama-cli -hf MaxedOut/ComfyUI-Starter-Packs:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf MaxedOut/ComfyUI-Starter-Packs:Q4_K_M # Run inference directly in the terminal: llama-cli -hf MaxedOut/ComfyUI-Starter-Packs:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf MaxedOut/ComfyUI-Starter-Packs:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf MaxedOut/ComfyUI-Starter-Packs:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf MaxedOut/ComfyUI-Starter-Packs:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf MaxedOut/ComfyUI-Starter-Packs:Q4_K_M
Use Docker
docker model run hf.co/MaxedOut/ComfyUI-Starter-Packs:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use MaxedOut/ComfyUI-Starter-Packs with Ollama:
ollama run hf.co/MaxedOut/ComfyUI-Starter-Packs:Q4_K_M
- Unsloth Studio
How to use MaxedOut/ComfyUI-Starter-Packs with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for MaxedOut/ComfyUI-Starter-Packs to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for MaxedOut/ComfyUI-Starter-Packs to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MaxedOut/ComfyUI-Starter-Packs to start chatting
- Docker Model Runner
How to use MaxedOut/ComfyUI-Starter-Packs with Docker Model Runner:
docker model run hf.co/MaxedOut/ComfyUI-Starter-Packs:Q4_K_M
- Lemonade
How to use MaxedOut/ComfyUI-Starter-Packs with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MaxedOut/ComfyUI-Starter-Packs:Q4_K_M
Run and chat with the model
lemonade run user.ComfyUI-Starter-Packs-Q4_K_M
List all available models
lemonade list
Create README.md
Browse files
README.md
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| 1 |
+
# Best-Models-For-ComfyUI
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> A curated vault of the most essential, powerful, and optimized models for ComfyUI users. Flux1, SDXL, ControlNets, Clips, GGUFsβall in one place. Carefully organized. Pre-tested. One-click ready.
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---
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## πͺ What's Inside
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This repo is not a chaotic dumping ground. Itβs a **purposeful collection** of the most important ComfyUI-compatible models:
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### Flux1
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- **Unet Models**: Dev, Schnell, Depth, Canny, Fill
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- **GGUF Versions**: Q3, Q5, Q6 for each major branch
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- **Clip + T5XXL** encoders (standard + GGUF versions)
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- **Loras**: Only when there's actual value (e.g. not bloated or redundant)
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### SDXL
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- **Top Models** from Civitai (Realism, Stylized, Experimental)
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- **Base + Refiner** official models
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- **ControlNets**: Depth, Canny, OpenPose, Normal, etc.
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### Extra
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- VAE, upscalers, and anything required to support workflows
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---
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## ποΈ Unet Recommendations (Based on VRAM)
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| VRAM | Use Case | Model Type |
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|------|----------|-------------|
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| 16GB+ | Full-quality FP8 | flux1-dev-fp8.safetensors |
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| 12GB | Balanced Q5_K_S | GGUF flux1-dev-Q5_K_S.gguf |
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| 8GB | Light Q3_K_S | GGUF flux1-dev-Q3_K_S.gguf |
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GGUF models are significantly lighter and designed for **low-VRAM** systems.
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## π§ T5XXL Recommendations (Based on Ram)
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| System RAM | Use Case | Model Type |
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|------------|----------|-------------|
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| 64GB | Max quality | t5xxl_fp16.safetensors |
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| 32GB | High quality (can crash if multitasking) | t5xxl_fp16.safetensors |
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| 16GB | Balanced | t5xxl_fp8_scaled.safetensors |
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| <16GB | Low-memory / Safe mode | GGUF Q5_K_S or Q3_K_S |
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> β οΈ These are **recommended tiers**, not hard rules. RAM usage depends on your active processes, ComfyUI extensions, batch sizes, and other factors.
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> If you're getting random crashes, try scaling down one tier.
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---
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## π Folder Structure (Flux1 Only)
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```
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Flux1/
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ββ unet/
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β ββ Dev/
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β β ββ flux1-dev-fp8.safetensors
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β β ββ GGUF/
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β ββ Schnell/
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β ββ Depth/
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β ββ Canny/
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β ββ Fill/
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ββ clip/
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β ββ t5xxl_fp16.safetensors
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β ββ GGUF/
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β ββ ...
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ββ loras/
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```
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---
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## π Model Previews (Coming Soon)
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We will add a single grid-style graphic showing example outputs:
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- **Dev vs Schnell**: Quality vs Speed
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- **Depth / Canny / Fill**: Source image β processed map β output
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- **SDXL examples**: Realism, Stylized, etc.
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All preview images will be grouped into a single efficient visual block for each group.
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---
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## π’ Want It Even Easier?
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Skip the manual downloads.
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π **[Patreon.com/MaxedOut](https://patreon.com)** β Get:
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- One-click installers for all major Flux & SDXL workflows
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- Organized ComfyUI folders built for beginners and pros
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- Specialized templates (e.g. Mega Flux, Tiled Composites, Realistic Portraits)
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- Behind-the-scenes model picks and tips
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---
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## β FAQ
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**Q: Why not every GGUF?**
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A: Because Q3, Q5, and Q6 cover the most meaningful range. No bloat.
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**Q: Are these the official models?**
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A: Yes. Most are sourced directly from creators, or validated mirrors.
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**Q: Will this grow?**
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A: Yes. But only with purpose.
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---
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## β¨ Final Thoughts
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You shouldnβt need to hunt through 12 Discord servers and 6 Civitai pages just to build your ComfyUI folder.
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This repo fixes that.
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**The Best Models. For ComfyUI. In One Place.**
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