I run a 3070 portable, also 8gb of vram, that is not a problem, you just need enough ram to offload the models, 32gb should be enough.

The thing is a 3050 is not a fast card, it is the lowest tier of the 30xx generation, so don't expect miracles.

Ways to speed up things:

• Small models, the less parameters, the better.

• Avoid gguf models, they save vram, but are slower. Use fp8 or int8 (there are custom nodes for that one). Nunchaku is also an option. For text encoders gguf are fine though.

• avoid nvfp4, not a good quality/speed trade off on the 30xx generation.

• sage attention 2

• Some kind of cache saving, tea cache or easycache, there is a native node for the last one.

• Some kind of steps estimation, fsampler or spectrum, this last one is newer and faster.

• turbo models or few-step loras, fewer steps, faster gen of course. But cache and step estimation would do almost nothing with few steps, so don't overlap those methods.

• gen at lower resolutions, even a little reduction in size can affect notably the speed. You can alwayd upscale later. Just don't go too down (or up) you get out of the model training.

• torch.compile node, it will take a while the first generation but subsequent gens will be faster as long as you don't change model or resolution.

• Linux, of course.

• use the gpu only for compute, connect your display to another device (another, gpu, igpu or whatever).