Hey!
If your machine is solid—especially the GPU—you should be able to get great results. If you’re finding limitations with Stable Diffusion, it might not be the model itself, but rather how you’re using it. Don’t worry—there’s a bit of a learning curve, but once you get the hang of it, things improve a lot!
First off, no single model will cover everything perfectly. Models are usually trained to excel in specific areas, and combining them with LoRAs (Low-Rank Adaptations) can really help fine-tune for particular outputs. However, trying to make a model generate something outside its training will almost always lead to frustration. For photorealistic faces (especially avoiding that dreaded uncanny valley), it’s all about patience, experimentation, and the right tools.
If you’re on SD1.5, I’d suggest starting with models like Juggernaut or Realistic Vision. Both are on Civitai and are fantastic for photorealistic results when paired with good prompts. They’re versatile enough to get nice outputs, but you’ll still need to spend time tweaking to get exactly what you want.
That said, if you’ve got a beefy setup, consider trying Flux. It’s known for producing some seriously impressive results with photorealistic outputs—especially when paired with the right tools like LoRAs and upscalers. It might just solve some of the limitations you’re running into.
To get truly polished and realistic faces, tools like CodeFormer or GFPGAN are must-haves. These are excellent for refining and restoring facial details, taking your results from “almost there” to “wow!”
Seriously, they’re game-changers.
Now, for your earlier frustration with other types of content (like penises): the same principle applies. Combining multiple specialised LoRAs and adjusting their weights can work wonders, but again, it’s all about experimenting with combinations, weights, and prompts. There’s no one-size-fits-all here—it’s trial and error.
Lastly, when writing prompts, keep an eye on the language. Models respond best to clear, descriptive phrasing that matches their training. If something isn’t working, switch up the wording and try again—it’s surprising how much difference that can make. Just keep testing—you’ll get there!
It’s all about patience, persistence, and playing around with your tools. You’ve got this!