Stable Diffusion - Mac vs RTX4090 vs RTX3060 vs Google Colab - how they perform.
TLDRIn this video, the creator compares the performance of Stable Diffusion on different systems, including a MacBook Pro M1 Max, a mid-range PC with an RTX 3060, a high-end PC with an RTX 4090, and Google Colab. The benchmarks include text-to-image and image-to-image tasks at various resolutions. The RTX 4090 outperforms all other systems, with nearly four times the performance of the RTX 3060 and five to six times that of the Mac. Google Colab, using an older Tesla T4 GPU, is less powerful but offers a free basic version and subscription plans with more powerful GPUs. The Mac struggles with high-resolution tasks and is not optimized for Stable Diffusion. The conclusion is that for those requiring significant computing power and willing to spend, the RTX 4090 is the top choice. For a mid-range system, the RTX 3060 is recommended. For budget-conscious users or those new to GPU-intensive tasks, Google Colab is suggested.
Takeaways
- 🖥️ The user compared Stable Diffusion performance on a Mac, RTX 3060, RTX 4090, and Google Colab.
- 🍎 The MacBook Pro M1 Max, despite its power, showed that Stable Diffusion is not yet optimized for Mac.
- 💻 A mid-range PC with an AMD Ryzen 5 and Nvidia RTX 3060 was found to perform well for certain tasks.
- 🚀 The high-end PC with a Ryzen 9 and RTX 4090 outperformed others, especially with high-resolution tasks.
- 🔋 RTX 4090 has a significant lead in performance but also has higher power consumption and cost.
- 💰 The RTX 3060 offers a good balance between cost and performance for mid-range projects.
- 🔧 Google Colab, using an older Tesla T4 GPU, was not as performant as the dedicated GPUs.
- 🧩 The user experienced errors with the Mac when using the Stable Diffusion model with high-resolution fixes.
- 📈 Benchmarks included text-to-image, image-to-image, and animation rendering at various resolutions.
- 📊 Results showed that RTX 4090 was the fastest, followed by RTX 3060, with Mac and Google Colab lagging behind.
- 📝 For those with a tight budget or who do not wish to invest heavily, Google Colab is suggested as an alternative.
Q & A
What is the main topic of the video?
-The video compares the performance of stable diffusion on different systems, including a Mac with M1 Max, a mid-range PC with an RTX 3060, a high-end PC with an RTX 4090, and Google Colab.
Why did the user switch from Mac to a PC with an RTX 3060?
-The user switched to a PC with an RTX 3060 because they needed to work on projects with the Unreal Engine, which doesn't work well on a Mac, and also wanted to use it for stable diffusion.
What is the primary reason the user decided to buy a PC with an RTX 4090?
-The user decided to buy a PC with an RTX 4090 to have more computing power to finish larger projects.
How does Google Colab help with demanding tasks without needing a powerful personal GPU?
-Google Colab provides access to Google's servers, which offer powerful GPUs for use in demanding tasks, eliminating the need for a personal powerful GPU.
What are the key specifications of the user's high-end PC with an RTX 4090?
-The high-end PC has a Ryzen 9 processor, an RTX 4090 GPU with 24 GB of VRAM, and 64 GB of RAM.
How many benchmarks did the user perform for the comparison, and what was the process?
-The user performed 9 benchmarks, each with five iterations, using the mean value of the last four iterations as the result for each benchmark.
What was the surprising result for the user regarding the Mac's performance with stable diffusion?
-The surprising result was that the Mac, despite having a powerful M1 Max chip with 32 GPU cores, showed significant performance issues with stable diffusion, indicating it is not yet optimized for Mac.
What issue did the user encounter when using the automatic 1111 version on the Mac?
-The user encountered an error when using the automatic 1111 version on the Mac, suggesting that it may not be compatible or there might be a configuration issue.
How did the RTX 4090 perform in image to image benchmarks with high resolutions?
-The RTX 4090 performed exceptionally well, showing no issues even with high resolutions, likely due to its 24 GB of VRAM and 64 GB of RAM.
What is the user's recommendation for someone with a tight budget interested in stable diffusion?
-For those with a tight budget, the user recommends considering an RTX 3060 or a similar mid-range GPU, or trying Google Colab, which offers a free basic version and subscription models.
What conclusion did the user come to regarding the best system for stable diffusion?
-The user concluded that the RTX 4090 is the best performer for stable diffusion, but it's also the most expensive. For a mid-range system, an RTX 3060 or similar is recommended. The user advises against buying a Mac solely for stable diffusion due to its current performance issues.
Outlines
🖥️ Mac vs. PC Performance on Stable Diffusion
The video script introduces a comparison of how Stable Diffusion performs on different systems. The creator, a long-time Mac user, initially used Stable Diffusion on a MacBook Pro M1 Max but later switched to a mid-range PC with an RTX 3060 for projects requiring Unreal Engine, which is not well-supported on Macs. The creator also mentions using Google Colab for demanding tasks. The video aims to compare the performance of the Mac, the mid-range PC, a high-end PC with an RTX 4090, and Google Colab. Benchmarks include text-to-image and image-to-image tasks with varying resolutions and models. The Mac's performance with Stable Diffusion is noted to be suboptimal, with the RTX 4090 showing the best results in the benchmarks.
📊 Benchmark Results and System Recommendations
The script continues with the results of the benchmarks, highlighting the superior performance of the RTX 4090, which completed tasks significantly faster than the RTX 3060 and other systems. Google Colab's performance was expectedly lower due to the use of an older GPU. The Mac struggled, particularly with higher resolutions and when using the automatic 1111 model, which even threw an error. The video concludes with recommendations: for those who need high computing power and can afford it, the RTX 4090 is the top choice. For a mid-range system, the RTX 3060 or similar is suggested. The Mac is not recommended for those specifically looking to use Stable Diffusion due to its current performance issues, despite being a powerful machine. For those on a tight budget, Google Colab is proposed as a cost-effective alternative.
Mindmap
Keywords
💡Stable Diffusion
💡Mac
💡RTX 4090
💡RTX 3060
💡Google Colab
💡Benchmarks
💡Apple Silicon
💡VRAM
💡RAM
💡Control Nets
💡High-Res Fix
Highlights
The video compares the performance of Stable Diffusion on different systems including Mac, RTX 3060, RTX 4090, and Google Colab.
The presenter used to work on a Mac but switched to a mid-range PC with an RTX 3060 for Unreal Engine projects and Stable Diffusion.
A high-end PC with an RTX 4090 was purchased for more powerful computing to handle larger projects.
Google Colab is used for demanding tasks like Dream Booth trainings for custom Stable Diffusion models.
The presenter conducted 9 benchmarks with five iterations each to assess performance.
Benchmarks include text-to-image and image-to-image tasks using different models and resolutions.
The RTX 4090 outperformed all other systems in the first benchmark, completing tasks in just 2.1 seconds.
The RTX 3060 was a close second in performance, taking 3.6 seconds for the same tasks.
Google Colab with a Tesla T4 GPU showed expectedly slower performance due to the GPU's age.
The Mac, despite having a powerful M1 Max chip, showed significant performance issues with Stable Diffusion.
At 768x768 resolution, the performance gap between systems widened, with RTX 4090 being the clear winner.
The RTX 4090 showed no performance issues even with high-res fix, unlike the other systems.
The Mac encountered errors when using the automatic 1111 version of Stable Diffusion, indicating potential compatibility issues.
For image-to-image tasks with control nets, the RTX 4090 maintained its lead, while the RTX 3060 and Google Colab performed well at lower resolutions.
The Mac struggled with high-resolution tasks, particularly using automatic 1111, and was the worst performer.
In the standard animation rendering test, the RTX 4090 was unbeatable at 512x512 pixels.
The RTX 4090 is recommended for those needing great computing power and willing to spend, despite its high power consumption and cost.
For a mid-range system, the RTX 3060 or similar is suggested as a good value option.
Google Colab is recommended for those with a low budget or who are unwilling to invest heavily in Stable Diffusion hardware.
The presenter concludes that the RTX 4090 is the best performer but advises against buying a Mac solely for Stable Diffusion purposes due to its performance issues.