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LoRA Training

Generated on PixelDojo with Flux 2 LoRA Trainer. Produced by PixelDojo's generation pipeline.

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To train a LoRA on your own photos you upload ten to twenty of them, write one caption that describes your subject, pick a step count, and start the run. On Pixel Dojo you do that on a hosted trainer, so there is no GPU to rent and no training script to configure, and the price is fixed per thousand steps: 32 credits on Flux Dev, 45 on Z-Image, and 160 on Flux 2. The default runs are 2,000 steps on Flux Dev for 64 credits, 2,000 steps on Z-Image for 90 credits, and 1,000 steps on Flux 2 for 160 credits. At the $0.0625 list price per credit, which Lite and the $5 to $100 credit packs charge, that is $4.00, about $5.63 and $10.00 respectively, and less on Pro, Pro Max or a bigger pack.

Four things that decide whether the run works

Captions decide what you can prompt later

The default caption you write at training time is the phrase that summons the LoRA afterwards. Use something you would never type by accident. A zip upload can also carry a .txt caption per image when different photos need different descriptions.

More steps is the most common mistake

The trainers ship sensible defaults, 2,000 steps on Flux Dev and Z-Image and 1,000 on Flux 2, and pushing well past them tends to overfit. An overfit LoRA reproduces its training photos and stops responding to the rest of your prompt, which is the opposite of what you trained it for.

Face sets and style sets are different jobs

For a face or a product, keep the subject the same and vary the angle, the lighting and the background. For a style, do the opposite: use different subjects that share one look, so the run learns the palette, brushwork and composition instead of a single scene. Picking the wrong kind of set wastes the whole run.

Price the experiment, not just the result

Your first LoRA on a new photo set is a test of the photo set. Run it on the 32 or 45 credit trainer, look at what came out, fix the set, and only move up to the 160 credit trainer once the photos are proven. That order costs less than being right on the first try elsewhere.

Every price, step count and photo-count guideline on this page was read out of the live trainer configuration on August 26, 2026, the same day the Flux 2 trainer was turned back on after a smoke training run passed end to end in 449.8 seconds. The Flux Dev figures were read the same way on October 1, 2026.

Why Choose Pixel Dojo for LoRA Training

Professional-quality results with cutting-edge AI technology

Z-Image trainer, 45 credits per 1,000 steps

It produces compact rank-16 LoRA files and most runs finish in well under an hour, so photos uploaded in the morning are generating by lunch. The default run is 2,000 steps, which comes to 90 credits, and the step range accepted goes from 10 up to 40,000.

Flux Dev trainer, 32 credits per 1,000 steps

The lowest price per step of the three, and the pick for photo-real portraits. It charges 16 credits per 500 steps, so the default 2,000-step run is 64 credits, and the accepted range is 500 to 4,000 steps in blocks of 500. Most runs finish in 30 to 60 minutes, and auto captioning can describe each training image for you when you are training a style.

Flux 2 trainer, 160 credits per 1,000 steps

The most expensive rung and the one to pick for premium character and product LoRAs, because the Flux 2 base renders text crisply and holds fine facial detail. The default is 1,000 steps for 160 credits, and the accepted range runs from 100 to 10,000 steps.

Z-Image and Flux 2 run on our own hardware

Those two trainers are self-hosted rather than brokered out, which is why they price at a flat rate per thousand steps instead of a variable compute bill. Whichever trainer you pick, your finished LoRA lands in your library and is usable directly in generation, with no weights to upload anywhere else.

How It Works

1

Collect ten to twenty photos

Ten or more good photos is the working minimum and ten to twenty is the guidance for a sharp likeness. Vary the angle, the lighting and the background, and keep the subject consistent. A set of twenty near-identical photos teaches less than a set of twelve varied ones.

2

Pick the trainer that matches your base model

Train on the model you intend to generate with, because a LoRA is tied to its base. Flux Dev at 32 credits per thousand steps for photo-real portraits, Z-Image at 45 for compact files you can use the same day, Flux 2 at 160 for the sharpest character and product detail.

3

Choose how the photos go in

Three ways. Upload a zip, which also accepts an optional .txt caption file per image. Upload up to thirty loose images and the zip gets built for you. Or bring a single photo to Character Studio, generate a full training set from it, pick the best shots, and send those back to the trainer.

4

Write the caption and set the steps

You give the run a display name and one default caption in the form of a photo of your subject in a given style. That caption is what you will prompt with later, so choose a word you would not otherwise type. Then set the step count. The defaults are deliberate, and higher is not better: too many steps overfits and the LoRA stops taking direction.

5

Start the run, then generate with it

Credits are charged when the run starts and the job is tracked until it finishes. Watch progress under My Trainings. When it lands, the LoRA appears in your library and is selectable in the generation tools straight away.

Turn a folder of photos into a model of your own

Loved by creators on PixelDojo

Real feedback from people using PixelDojo, pulled from our in-product surveys.

Because it is awesome
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exceptional quality and great overall design of platform and interface. very intuative. love the creative freedom.
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Qwen image 2 is amazing!!
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Creative freedom, range of tools and options.
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I love the training feature
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the quality is the best
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Common Questions

Everything you need to know about LoRA Training

How many photos does a LoRA actually need?

Ten or more high-quality photos works well, and ten to twenty is the guidance for a sharp likeness. The loose-image uploader accepts up to thirty. Variety matters more than volume: different angles, lighting and backgrounds teach the model what is essential about the subject and what is just the room it was standing in.

What does it cost to train one LoRA?

It is a flat rate per thousand steps. Flux Dev is 32 credits, charged as 16 per 500 steps, so a 500-step run is 16 and the 2,000-step default is 64. Z-Image is 45 credits, so a 500-step run is about 23 and the 2,000-step default is 90. Flux 2 is 160 credits, so 500 steps is 80 and 2,000 is 320. At the $0.0625 list price per credit, the Flux 2 default run is $10.00, or $8.00 at Pro's 5 cents a credit.

Which trainer should I pick for a face?

Flux Dev if you want photo-real portraits for 32 credits per thousand steps, or Flux 2 if you want the finest facial detail and are willing to pay 160 credits per thousand steps for it. Flux Dev and Z-Image are the ones to start on when you are still learning what your photo set needs, because a mistake there costs 32 or 45 credits per thousand steps instead of 160.

How long does training take?

Z-Image runs mostly finish in well under an hour. On the day we turned the Flux 2 trainer back on, our end-to-end smoke training completed in 449.8 seconds and produced a valid LoRA file. Longer step counts take proportionally longer, which is the other reason not to reach for a step count you do not need.

Can I train from a single photo?

Not directly, but there is a path. Take one photo into Character Studio, generate a consistent set of shots of that same subject, choose the ones that hold the likeness, and send those into the trainer as your training set. You are still training on a real set, it is just a set you generated.

What happens to the LoRA after training?

It lands in your library and becomes selectable in the generation tools immediately. You prompt it using the caption phrase you set at training time. Nothing needs exporting, hosting or wiring into an endpoint, and the file stays yours.

Check on a run you already started

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