How to choose an AI image model?
You do not choose a model before the project: you start from the expected result, from what will need correcting, from the hardware, the access (local or API) and the licence. The criterion everyone forgets: correction.
Choosing an AI image model starts with the expected result (the type of image, the realism, the style, the references available, the corrections to plan for, the destination) and only then with the engine. At Axiris, the most often forgotten criterion is correction: a model that generates well but cannot edit forces you to start everything over, whereas a professional must be able to rework one area without losing the rest. Hardware, local or API access and the licence close the choice; the model serves the workflow, not the other way round.
Too many models, one question: which one for this job?
The number of available models grows every month. For a creative, the problem is no longer getting access to an AI that can generate an image: it is choosing the engine suited to the project, and not building the project around an engine chosen in advance.
Start from the result
At Axiris, we first define what has to come out: the type of image, the level of realism, the style, the references available, the changes that will be requested, the level of control expected, the destination of the visual.
Only then do we choose the engine. The families we follow are presented in AI models for image creation, and what we use today in Models of the moment.
Generate or modify?
A model that performs very well in text-to-image is not necessarily the best at precisely modifying an existing image. A project may call for a full generation, an image-to-image transformation, instruction-guided editing, retouching by area, several references, keeping a character consistent.
The engines that can edit are presented in Image editing models.
The criterion everyone forgets: correction
An impressive first image has become easy to obtain. The real work starts afterwards: the client wants to keep the image and change a single element. A model that generates well but cannot edit then forces you to start over, and to lose what had been validated.
For a professional, being able to rework one area matters as much as the first image. That is the gesture of retouching by area: you mask, you say what you want, the engine works only there, the rest does not move. A model that does not allow it limits the workflow, whatever the quality of its first render.
Local or online service?
A model running on your own machine gives you control of the pipeline and keeps your files with you. A remote service gives access to a model that is impossible or costly to run yourself. Both have their place, and a workflow can combine them: Local AI model or API?.
The hardware available
Graphics memory, system memory, storage and GPU power rule out certain choices. A model that is excellent on paper is bad for your workflow if it makes every generation too slow: How much VRAM to generate AI images?.
The licence
Before bringing a model into professional production, you need to read its licence. Being able to download the weights does not mean every use is permitted: AI model licences.
The model is part of the workflow
The model takes its place in a wider chain: brief → references → model → generation → control → correction → finishing. At Axiris, we choose the model to serve the workflow; we do not build the workflow to serve the model. The next step is in AI workflow for creatives.
For a company, the choice may also not be yours to make: in the Nova service, Axiris chooses the engine for each task according to the confidentiality you have set. See Axiris for business.
Contact request: a first conversation, free and with no commitment. Every practice is different; it is by listening to you that we propose what suits you.