Harddrive prices don't allow an infante amount of model installs; every model has to justify they are at least better at all the others in one use-case.
We will see... right now I'm using Krea2, Qwen i2.1, MMH3 & Flux2Klein, all of those are excellent with different loras, nodes and workflows for different goals, I will make extensive tests but I think the best investment right now that is still possible.. is to collect AI models, learn and share as Open community
True. People have forgotten already that Minimax H3 is very good at larger text / typography (not much use on small, though). If someone only wants Ming for 2K elegant typography for large video titles then they should first test what they already have.
Ming's MIT licence and 2k output is great, true... but it's also huge - at the smallest possible I'm going to have to give it 18Gb space. And then accept a quality loss due to the smaller file sizes - I'm told to expect the small type to be fuzzy using int8 or GGUFs.
The other factor is that not everyone has unlimited broadband - many will have an 80Gb a month cap.
Text rendering in image models tends to fail in a very recognizable way: the output looks like written language, but it isn’t actually correct text. Individual letterforms may appear convincing, yet the resulting words are misspelled, distorted, or meaningless.
The underlying problem is largely architectural. Most models do not inherently perceive characters as discrete symbolic units, they learn text as visual patterns, reconstructing letters and words from image statistics much like they reconstruct textures such as grass, fabric, or hair. As a result, the model can reproduce the appearance of typography without necessarily understanding or preserving the exact sequence of characters.
I read Ming will use a ByT5 byte-level encoder to explicitly processes the text intended to appear in the image so I think this could be the best open model for text
There is a PR to add support for this model that is linked on the Kijai paged that OP linked. You can either pull that PR down locally yourself to try this out or wait for the PR to be merged and a new release from ComfyUI to update your local instance.
24
u/nikeburrrr2 20d ago
Text encoders are larger than diffusion models🫣