AI Image Generators
Posted: Tue Jul 08, 2025 12:46 pm
This thread is for those who want to have full control over what they create using AI image generators and to hopefully gain insight from other users. I am not an expert so I can only offer insight from my own experience with such programs. I still don't like forums being flooded with images from generators but the programs can be useful in creating my own art, especially manips.
OK, this turned out to be disappointing for me because I have an Intel Mac Pro with dual AMD GPUs, which has plenty of power, RAM and VRAM to run machine learning apps. The problem is the model coding (Xcode on Macs). From what I've learned so far, the Mac versions of these apps are written for ARM architecture (M-series chips) and other versions are optimized for CUDA architecture (NVIDIA GPUs) in a Linux or Windows environment. It's a double whammy for me because I have neither. I may install Linux in a dual boot configuration in the future but for now I can only speak from a MacOS point of view. I haven't used Windows in 10 years.
The following is from my personal experience with MacOS running FREE AI image generators locally (offline only) and not WebUI cloud based generators which are subject to censorship.
There are a few reasons why my system is not compatible with AI image generators e.g. text to image, image to image, etc.
1. My system is high-end but does not have ARM architecture, it is a x64 Intel system.
2. NVIDIA GPUs have what's called, "tensor cores" which are designed to accelerate deep machine learning.
3. AMD GPUs do not have tensor cores.
Offline AI image generators for MacOS that I've tested are designed for M-series (Apple Silicon) chips but can be run on some non-silicon systems, but the caveat will be poor performance and much slower rendering times. So far all of the generators I've tested consumed 100% of VRAM (single GPU with 16GB VRAM) and crashed when using LLMs. So far none of them recognize multi-GPU systems and will only recognize one of the GPUs.
The following are the results from testing on my 2019 Mac Pro | 2TB Apple SSD (1.5TB free) | 3.2GHz 16-Core Intel Xeon | 96GB DDR4 | Dual Radeon RX 6900 XT (16GB x 2) | MacOS Sequoia 15.5.
During testing I tried out several models in each app before making my determination.
1. Draw Things AI: Fails to render anything except random noise, no image.
2. DiffusionBee: Fails to render anything except random noise, no image.
3. Easy Diffusion: Runs locally in Terminal using browser API, Poor performance because it runs on CPU and does not recognize GPU, Does not render prompts accurately, Some prompts are completely ignored resulting in a very random and distorted image, very slow. poor image quality, Text to image and image to image only, no video. Not worth using because it's not compatible with AMD GPUs in MacOS environment. The work around would be to install Linux or Windows.
4. Diffusers: Text to image only, Very fast, Non-verbose prompts generate a decent quality image in just a few seconds, Very limited models to choose from, some models ignore prompts resulting in random image noise, Eventually crashes because it does not release VRAM after each generation.
5. Stable Diffusion web UI: Runs locally in browser API, May need to install Windows with DirectML, Not tested yet.
6. ComfyUI: Not tested yet.
7. AUTOMATIC1111: Not supported on Intel Macs but user claims altering scripts enables it to run on CPU: https://github.com/AUTOMATIC1111/stable ... 1290150405
After further research, this is a work in progress: https://www.tomshardware.com/software/a ... her-things
OK, this turned out to be disappointing for me because I have an Intel Mac Pro with dual AMD GPUs, which has plenty of power, RAM and VRAM to run machine learning apps. The problem is the model coding (Xcode on Macs). From what I've learned so far, the Mac versions of these apps are written for ARM architecture (M-series chips) and other versions are optimized for CUDA architecture (NVIDIA GPUs) in a Linux or Windows environment. It's a double whammy for me because I have neither. I may install Linux in a dual boot configuration in the future but for now I can only speak from a MacOS point of view. I haven't used Windows in 10 years.
The following is from my personal experience with MacOS running FREE AI image generators locally (offline only) and not WebUI cloud based generators which are subject to censorship.
There are a few reasons why my system is not compatible with AI image generators e.g. text to image, image to image, etc.
1. My system is high-end but does not have ARM architecture, it is a x64 Intel system.
2. NVIDIA GPUs have what's called, "tensor cores" which are designed to accelerate deep machine learning.
3. AMD GPUs do not have tensor cores.
Offline AI image generators for MacOS that I've tested are designed for M-series (Apple Silicon) chips but can be run on some non-silicon systems, but the caveat will be poor performance and much slower rendering times. So far all of the generators I've tested consumed 100% of VRAM (single GPU with 16GB VRAM) and crashed when using LLMs. So far none of them recognize multi-GPU systems and will only recognize one of the GPUs.
The following are the results from testing on my 2019 Mac Pro | 2TB Apple SSD (1.5TB free) | 3.2GHz 16-Core Intel Xeon | 96GB DDR4 | Dual Radeon RX 6900 XT (16GB x 2) | MacOS Sequoia 15.5.
During testing I tried out several models in each app before making my determination.
1. Draw Things AI: Fails to render anything except random noise, no image.
2. DiffusionBee: Fails to render anything except random noise, no image.
3. Easy Diffusion: Runs locally in Terminal using browser API, Poor performance because it runs on CPU and does not recognize GPU, Does not render prompts accurately, Some prompts are completely ignored resulting in a very random and distorted image, very slow. poor image quality, Text to image and image to image only, no video. Not worth using because it's not compatible with AMD GPUs in MacOS environment. The work around would be to install Linux or Windows.
4. Diffusers: Text to image only, Very fast, Non-verbose prompts generate a decent quality image in just a few seconds, Very limited models to choose from, some models ignore prompts resulting in random image noise, Eventually crashes because it does not release VRAM after each generation.
5. Stable Diffusion web UI: Runs locally in browser API, May need to install Windows with DirectML, Not tested yet.
6. ComfyUI: Not tested yet.
7. AUTOMATIC1111: Not supported on Intel Macs but user claims altering scripts enables it to run on CPU: https://github.com/AUTOMATIC1111/stable ... 1290150405
After further research, this is a work in progress: https://www.tomshardware.com/software/a ... her-things