How to Download FLUX.1 Kontext: Complete Installation Guide (2025)

FLUX.1 Kontext is Black Forest Labs' latest AI image editing model that lets you edit photos with simple text commands. Here's your complete guide to downloading and setting it up.

Quick Overview: What You're Getting

FLUX.1 Kontext is a 12 billion parameter AI model that edits images using plain English instructions. Released in January 2025, it's available in multiple formats depending on your technical needs and use case.

Method 1: Web-Based Access (No Download Required)

The easiest way to start using FLUX.1 Kontext is through API services. No installation, no technical setup:

Recommended Platforms:

• fal.ai: https://fal.ai/flux-kontext
• Replicate: https://replicate.com/black-forest-labs/flux-kontext-dev
• DataCrunch: https://datacrunch.io/managed-endpoints/flux-kontext
• TogetherAI: https://www.together.ai/models/flux-1-kontext-dev
• Runware: https://runware.ai/blog/introducing-flux1-kontext-instruction-based-image-editing-with-ai

Pros: Instant access, no hardware requirements, always updated Cons: Requires internet, potential usage costs, less customization

Method 2: Direct Model Download via Hugging Face

Step 1: System Requirements

• GPU: CUDA-compatible graphics card (8GB+ VRAM recommended)
• RAM: 16GB minimum
• Storage: ~24GB free space
• Python: 3.8 or higher

Step 2: Install Dependencies

# Install diffusers from main branch
pip install git+https://github.com/huggingface/diffusers.git

# Install additional requirements
pip install torch torchvision torchaudio
pip install transformers accelerate

Step 3: Download the Model

Visit https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev

1. Accept the license agreement (FLUX.1 dev non-commercial license)
2. Share your contact information as required
3. Download manually or use the code below:

from diffusers import FluxKontextPipeline
import torch

# This will automatically download the model
pipe = FluxKontextPipeline.from_pretrained(
    "black-forest-labs/FLUX.1-Kontext-dev",
    torch_dtype=torch.bfloat16
)

Step 4: Basic Usage

from diffusers.utils import load_image

pipe.to("cuda")
input_image = load_image("your_image.png")

image = pipe(
    image=input_image,
    prompt="Add a hat to the cat",
    guidance_scale=2.5
).images[0]

image.save("edited_image.png")

Method 3: ComfyUI Integration

Installation Steps:

1. Install ComfyUI if you haven't already
2. Update ComfyUI to the latest version
3. Install FLUX.1 Kontext nodes through ComfyUI Manager
4. Download model files to your ComfyUI models folder

Model File Locations:

• Place model files in: ComfyUI/models/diffusion_models/
• Ensure proper file permissions and folder structure

Method 4: GitHub Repository

For developers wanting the complete implementation:

1. Clone the official repository:

git clone <https://github.com/black-forest-labs/flux>
cd flux

1. Install requirements:

pip install -r requirements.txt

1. Download model weights from Hugging Face as described in Method 2

Important Setup Notes

Content Safety Filter

Install the official safety checker:

pip install git+https://github.com/black-forest-labs/flux.git

License Requirements

• Non-commercial use only for the dev version
• Contact sharing required with repository authors
• Content filters mandatory under license terms

VRAM Optimization

For lower VRAM systems:

# Enable CPU offload
pipe.enable_model_cpu_offload()

# Use lower precision
pipe = FluxKontextPipeline.from_pretrained(
    "black-forest-labs/FLUX.1-Kontext-dev",
    torch_dtype=torch.float16  # instead of bfloat16
)

Troubleshooting Common Download Issues

Authentication Errors

• Ensure you've accepted the license on Hugging Face
• Log in with: huggingface-cli login
• Verify your account has access permissions

Storage Issues

• Model requires ~24GB total space
• Use torch_dtype=torch.float16 to reduce memory usage
• Consider using low_cpu_mem_usage=True during loading

CUDA Errors

• Update GPU drivers
• Verify CUDA installation: python -c "import torch; print(torch.cuda.is_available())"
• Install appropriate PyTorch version for your CUDA version

Next Steps After Download

1. Test basic functionality with a simple image edit
2. Experiment with different prompts to understand capabilities
3. Check out community examples on Hugging Face Spaces
4. Read the technical paper for advanced usage: arXiv:2506.15742

The model is now ready for use. Start with simple edits like "add sunglasses" or "change the background color" to get familiar with the prompt format and capabilities.