You Can Now Train Flux Image Models on RenderNet AI

Training an image model to generate custom AI photos used to be a long and tedious process. You needed several high-quality images and would often have to wait hours for your fine-tuned model to be ready.

But things have changed.

Today, fine-tuning image models has become much more efficient. With Black Forest Labs’ most powerful open-weight model, you can now train using just a single image. The training speed has also improved dramatically—what once took hours can now be done in just minutes.

Training Flux models with a single image is now available on one of the most popular image and video generation platforms, RenderNet.

In this article, I will walk you through the process of fine-tuning flux models with a single reference image and generating custom images.

Let’s get started.

What is RenderNet?

RenderNet is a generative AI platform known for its AI influencers or virtual character generation. With its Character Wizard, you can quickly design custom AI characters tailored to your needs. Once created, you can use prompts and the PoseControl feature to fine-tune their poses and composition with precision.

Recently, RenderNet added support for Flux models, which is a long awaited feature from fans, including myself.

What is Flux?

Flux is a powerful set of models from Black Forest Labs that takes text-to-image generation to the next level. It sets a new standard for image detail, accuracy, style variety, and complexity in scenes.

Here are the three versions of Flux:

• Flux.1 Pro: The best-performing model, offering top-quality images with excellent detail, prompt accuracy, and diverse styles.
• Flux.1 Dev: This version is open-weight and made for non-commercial use. It’s based on Flux.1 Pro and delivers similar quality but with improved efficiency, making it perfect for research and development.
• Flux.1 Schnell: The fastest model, designed for personal use and local development. It’s available for free under an Apache 2.0 license and works quickly without compromising quality.

All Flux models use advanced AI technology, featuring 12 billion parameters. They improve on older models by using a method called flow matching, which makes training easier.

They also include rotary positional embeddings and parallel attention layers to better use hardware, making the models faster and more efficient.

How to Create A Character

Getting started with Flux on RenderNet is simple and user-friendly. First, head over to the website and create a free account.

Flux is conveniently placed on the homepage. To begin, just click on the “Try Flux” button, and a modal window will be displayed.

Now, you have two options: choose a pre-set character or upload your own photo. If you’re looking to create something unique with a personal touch, I recommend going with your own image.

Head back to the homepage and click on the “Create New” button.

Upload your portrait photo. Make sure the face and the hair are clear. The system needs this clarity for better results when generating images.

Crop the photo as necessary to focus on the face. The accuracy of the crop can impact the final output, so pay attention to how well-defined the face and hair are.

Click on the “Next” button. This brings you to a customization window where you can adjust the character’s style, gender, age, and hair color/style. These parameters allow you to tweak the final result according to your creative needs.

Finally, give your character a name. This step is important because the name will act as a “trigger word” for the Flux model when generating images.

Once you’ve completed this, your new character will be added to your homepage’s character list, ready for you to use in image generation.

Awesome. Now, let’s try to use it to generate our custom images.

Creating Custom Images with Flux

The image generation dashboard is incredibly straightforward, even for beginners. At the bottom of the dashboard, you’ll notice a prompt field where you input the description of the image you want to generate. This is where the magic happens!

Let’s say you want your character to pose in a specific setting. Here’s an example:

Prompt: @Jade posing in the streets of new york

After setting your prompt, click the “Generate” button, and within a few seconds, the system will process and generate the image.

Pretty cool, right?

The results are impressive — Jade’s face, hair, and body stay remarkably similar to the input image. However, I noticed that while the overall photorealism is good, there’s still room for improvement in some details. The skin texture, lighting, and background integration can sometimes feel a bit off, especially compared to high-end models like Midjourney.

As you might have noticed, the name “@Jade” is included in the prompt. This is crucial, as it acts as the trigger word for the Flux model.

But what exactly is a trigger word?

In simple terms, a trigger word is a keyword tied to a specific object, style, or concept during the training phase of a model. In this case, “Jade” refers to the particular character or look that the model was fine-tuned on. When you include this trigger word in your prompt, the model knows to use that character for the generation.

This is one of the reasons why the generated images maintain consistency in the character’s appearance across different scenarios. Discard the trigger word, and you’ll get a completely different image.

Let’s try more examples.

Prompt: @Jade on top of mount everest wearing a puffy jacket

I was impressed with the level of coherency between the text prompt and the generated image. Not only did Flux manage to capture the harsh, snowy environment of Mount Everest, but it also made sure that the character was fully consistent with the original photo, even down to the facial features.

Prompt: @Jade wearing a dress and posing in a red carpet

What I love about this tool is the variation in the generated images while keeping the core elements consistent. The limbs, which are often tricky for AI generators, looked accurate, and the facial consistency from the input image was maintained.

While many AI image generators struggle with hands and fingers, Flux did a decent job here. I could see that the hands were properly defined and didn’t suffer from the usual awkwardness that you often see in AI-generated art.

Okay, now let’s talk about pricing.

How Much Does It Cost?

One of the best things about Flux on RenderNet is that it offers flexibility when it comes to pricing. Free-tier users get 10 free daily credits.

• Free: $0/month
  Includes 50 credits with up to 10 Flux images and 50 SDXL images. Limited features and 2 simultaneous generations.
• Basic: $9/month
  Provides 400 credits, up to 80 Flux images, and 400 SDXL images. Offers 1.5 minutes of Narration Video, 8K upscale, True Touch, and 2 simultaneous generations.
• Standard: $24/month
  Grants 2,000 credits with up to 400 Flux images and 2,000 SDXL images. Includes 8 minutes of Narration Video, 10 simultaneous generations, and all advanced features.
• Plus: $49/month
  Comes with 5,000 credits, up to 1,000 Flux images, 5,000 SDXL images, 20 minutes of Narration Video, and 50 simultaneous generations. Full access to all features.

If you plan on using Flux long-term, opting for an annual plan could save you some money. By paying annually, you’ll receive a 20% discount on any plan, which is a solid deal if you’re a regular user of the platform.

Why Should You Care?

Flux image models have proven to be among the most capable since their release two months ago. The image quality is impressive, the coherency with the text prompt is already really good, and its ability to render text accurately is mind-blowing.

In my opinion, Flux Pro is already as good as, if not better than, the most capable closed-source image generator, Midjourney. And since Flux is open-weight, fine-tuning it is possible, and now hundreds of platforms have made it available to their users.

Another fun fact is that the team behind Flux, Black Forest Labs, is made up of the original developers of the technology that powers Stable Diffusion and the inventors of latent diffusion. Stability AI had some internal issues in the past, which led its key team members to leave and form a new startup.

This kind of tech exodus often leads to innovation. When talented individuals branch out on their own, they’re free to pursue bold new ideas without the constraints of larger organizations.

Flux models are just a few months old, and this is only the first iteration. We can expect more exciting updates in the coming months. The team has also teased upcoming video models, which is even more exciting! RenderNet is also a video platform, so when the integration of Flux models happens, it’s going to be epic.

Final Thoughts

Overall, I’m glad to see RenderNet quickly adding support for Flux on its platform. I’ve been using RenderNet to generate talking AI influencers for a while now, and I’ve been satisfied with the results. The addition of Flux makes RenderNet an even more enticing platform for your AI image and video workflows.

The use cases could extend beyond portrait generation too. Flux image models can be fine-tuned with other subjects, not just human portraits. You can train it with photos of pets or products, meaning you can elevate your brand assets. Imagine training a model with just one photo of your product and generating unlimited variations in any design you can think of. How cool is that?

There are so many possibilities in the near future. I’m sure the developers at RenderNet are already working on exciting new features, and I can’t wait to see them get released!