Best GPUs for Stable Cascade and Diffusion - 2024

Pixovert
23 Feb 202413:22

TLDRKevin from pixel.com discusses the best GPUs for running Stable Cascade and Stable Diffusion models. He recommends at least 12 GB of VRAM for GeForce gaming cards and highlights the differences between Stable Cascade and Stable Diffusion. Kevin suggests the RTX 360 12 GB, RTX 4060 TI 16 GB, and the RTX 490 as top choices, with the latter being ideal for gaming and handling large Cascade models. He also mentions the upcoming Stable Diffusion 3 with models ranging from 800 million to 8 billion parameters.

Takeaways

  • 🚀 Kevin from pixel.com discusses the best GPUs for Stable Cascade and Diffusion in 2024.
  • 📈 Stable Cascade has higher requirements than stable diffusion, with a recommended 20 GB of VRAM.
  • 🔧 Kevin's testing found that 12 GB of VRAM could work for certain GeForce gaming cards with specific installations.
  • 📉 The quality of output may decrease when using smaller variants of Stable Cascade models.
  • 🎯 The focus is on achieving higher quality than stable diffusion, not just using less powerful models.
  • 🛠️ Community members have started producing their own third-party models for Stable Cascade.
  • 💰 Maxon, a new company from China, offers a three-fan GPU with good feedback on Amazon.
  • 💸 The RTX 360 12 GB is an older card but still popular; however, it's a bit expensive for its age.
  • 🚀 For better performance, Kevin recommends the 16 GB variant of the RTX 4060, which offers more CUDA cores and VRAM.
  • 🌟 The RTX 490 is the top recommendation for a gaming card capable of handling stable diffusion and large models from Cascade.

Q & A

  • What are the main graphics cards discussed in the video for stable Cascade and stable diffusion?

    -The main graphics cards discussed are the RTX 360 12 GB, Maxon's three-fan solution, RTX 4060 TI 16 GB, MSI gaming card, MSI gaming X slim, RTX 4070 TI Super, MSI RTX 480 Super Gaming X Trio, and the RX 490 24 GB.

  • What is the minimum VRAM suggested by Stability AI for stable Cascade?

    -Stability AI initially suggested a minimum of 20 GB of VRAM for stable Cascade.

  • How has the speaker managed to reduce the VRAM requirement for stable Cascade below the initially suggested 20 GB?

    -The speaker has managed to reduce the VRAM requirement by using specific installations that are good at memory management and limiting workflows to those that can work with lower amounts of memory.

  • What is the significance of the 3.6 billion parameter files for stage C and the 1.5 billion parameter models for Stage B in stable Cascade?

    -These larger files are used for higher quality outputs in stable Cascade, and the speaker prefers to use these over less powerful models to maintain a quality level higher than stable diffusion.

  • How does the community's creation of third-party models affect the VRAM requirements for stable Cascade?

    -The community's third-party models can vary greatly in size, with some reaching up to 34 GB for stage C, which may require more VRAM and affect the overall system requirements.

  • What is the price difference between the RTX 360 12 GB and the RTX 4060 TI 16 GB?

    -The price difference between the RTX 360 12 GB and the RTX 4060 TI 16 GB is about $100.

  • What are the key features of the MSI gaming X slim card?

    -The MSI gaming X slim card has 16 GB of VRAM, a somewhat faster speed, and is designed to fit in smaller cases.

  • Why is the RTX 4070 TI Super recommended over the entry-level cards?

    -The RTX 4070 TI Super has more powerful Cuda cores and a larger memory bandwidth, providing better performance than the 4060 TI 16 GB, making it a better choice for those willing to stretch their budget.

  • What is the main advantage of the RTX 480 Super Gaming X Trio over the 4060 TI 16 GB?

    -The RTX 480 Super Gaming X Trio is more powerful than the 4060 TI 16 GB, somewhat more powerful than the 470 TI super, and significantly less expensive than the 4080, offering a good balance of performance and cost.

  • Why might someone consider the RTX 490 24 GB over other cards for stable diffusion?

    -The RTX 490 24 GB is recommended for handling very large models from Cascade and provides ease in handling stable diffusion (sdxl). It is currently the best gaming card available for stable diffusion tasks.

Outlines

00:00

📌 Introduction to Graphics Card Recommendations for Stable Cascade and Diffusion

The video script begins with Kevin from pixel.com introducing the topic of graphics card recommendations for Stable Cascade and Stable Diffusion. He explains that Stable Cascade is a model from Stability AI that, while similar to Stable Diffusion, has more challenging requirements. Kevin mentions his experience with the software and the recommended 20 GB of VRAM, which he has managed to reduce through testing. The script also touches on the potential for using smaller variants of the Stable Cascade model and the importance of quality over using less powerful models. Kevin mentions his preference for higher quality output and the use of 3.6 billion parameter files for Stage C and 1.5 billion parameter models for Stage B.

05:02

💻 Graphics Card Options and Considerations

In this paragraph, Kevin discusses various graphics card options suitable for Stable Cascade and Stable Diffusion. He starts with the RTX 360 12 GB variant, noting its popularity and the existence of new revisions. Kevin then introduces Maxon, a company from China with a three-fan solution graphics card that has received positive feedback. He also mentions the Zotac card as a cheaper option and the MSI gaming card with its three-fan design and better cooling. The paragraph highlights the importance of knowing the card's measurements and power requirements, with MSI's marketing approach being appreciated for its clarity. The discussion then moves to the RTX 460, TI super, which is a more powerful option with a higher price point but offers better performance.

10:04

🌐 UK Graphics Card Recommendations and Market Trends

The final paragraph focuses on the UK market and the availability of graphics cards. Kevin recommends the MSI RTX 480 super gaming X Trio, which offers powerful performance at a reasonable price point, and notes the popularity and demand for these cards in the United States. He also mentions the high prices in the US market and the more reasonable prices in the UK. The paragraph concludes with a discussion on the RTX 490, which is considered the top recommendation for a gaming card capable of handling Stable Diffusion and large models from Cascade. Kevin notes that while the RTX 490 is powerful, there may be better cards for training purposes. He wraps up by mentioning that he will provide links to more information on the recommended cards and other options in the video description.

Mindmap

Keywords

💡Graphics Cards

Graphics Cards, also known as GPUs (Graphics Processing Units), are critical components in computers that handle the rendering and display of images, videos, and animations. They are especially important for tasks that require intensive graphical computation like gaming, video editing, and running AI models. In the context of this video, the author is discussing the best GPUs for running specific AI models, Stable Cascade and Stable Diffusion, which require high-performance graphics cards to function optimally.

💡Stable Cascade

Stable Cascade is an AI model developed by Stability AI. It is similar to Stable Diffusion in some aspects but also has significant differences, including more challenging requirements. The model is used for generating high-quality images and is known for its ability to produce outputs that can surpass the quality level of Stable Diffusion. The video focuses on recommending GPUs that can effectively run Stable Cascade, with a particular emphasis on having sufficient VRAM (Video RAM) to handle the model's demands.

💡Stable Diffusion

Stable Diffusion is another AI model that is used for generating images from textual descriptions. It has gained popularity for its ability to create realistic and diverse visual outputs. While it shares some similarities with Stable Cascade, it has different requirements and capabilities. The video discusses the varying needs of these two models and provides GPU recommendations suitable for both.

💡VRAM

VRAM, or Video RAM, is the memory used by graphics cards to store image data that is being processed or rendered. The amount of VRAM a GPU has is crucial for running AI models like Stable Cascade and Stable Diffusion, as these models require a significant amount of memory to store and manipulate the large datasets involved in image generation. In the video, the author emphasizes the importance of having enough VRAM to ensure smooth operation of the AI models and provides recommendations based on the VRAM capacity.

💡GeForce

GeForce is a brand of graphics processing units (GPUs) produced by NVIDIA Corporation. These GPUs are widely used in gaming, professional visualization, and AI applications. In the context of the video, the author is discussing the performance of GeForce cards, specifically their VRAM capacity, in relation to running Stable Cascade and Stable Diffusion models. The GeForce series mentioned includes the RTX 360 and RTX 4060 TI, among others.

💡Maxon

Maxon is a company that produces GPUs, and in the context of this video, the author mentions a specific model from Maxon that has caught their attention. The Maxon card is noted for its three-fan solution and positive feedback on Amazon. While the author does not provide extensive details about Maxon, they express a liking for the company's product offerings and design, including the use of purple on their packaging, which might suggest a positive brand image.

💡RTX 4060 TI

The RTX 4060 TI is a specific model of graphics card that falls under NVIDIA's 40 series GPUs. It is mentioned in the video as a recommended upgrade from the older RTX 360, offering more CUDA cores and additional VRAM, which significantly improves performance for tasks like running AI models. The 16 GB variant of the RTX 4060 TI is highlighted as a good starting point for those looking to invest in a more powerful GPU for Stable Diffusion and Stable Cascade.

💡MSI

MSI, or Micro-Star International, is a company known for its computer hardware products, including graphics cards. In the video, the author mentions several MSI gaming cards, noting their features such as three-fan variants for better cooling and higher clock speeds. The MSI brand is associated with quality and performance, and the author appreciates the detailed product information provided by MSI, including the card's size and power requirements.

💡RTX 4080

The RTX 4080 is a high-end graphics card model from NVIDIA's 40 series, designed for powerful performance in gaming and other demanding applications. In the video, the author discusses the RTX 4080 in the context of its price and performance, noting that it is more expensive than the RTX 4070 TI but offers significant power and is capable of handling both Stable Cascade and Stable Diffusion models with ease.

💡RTX 490

The RTX 490, with 24 GB of VRAM, is a top-of-the-line graphics card from NVIDIA, designed to handle the most demanding tasks, including running large AI models and gaming. The video highlights the RTX 490 as the best gaming card for stable diffusion, capable of managing very large models from Stable Cascade. However, it is noted that while the RTX 490 is powerful, there may be better cards available for training purposes.

💡Amazon Layaway

Amazon Layaway is a payment plan offered by Amazon that allows customers to pay for items in installments over time. This service can be beneficial for those who want to purchase high-priced items like graphics cards but may not have the full amount available at once. The video mentions Amazon Layaway as a potential option for viewers who find the recommended GPUs to be expensive and need a more manageable payment plan.

💡eBay

eBay is an online marketplace where individuals and businesses can buy and sell goods and services. In the context of the video, the author mentions eBay as a platform where viewers can sell their previous graphics cards if they are looking to upgrade to a newer model. This can help offset the cost of purchasing a more powerful GPU recommended for running Stable Cascade and Stable Diffusion.

Highlights

Kevin from pixel.com provides recommendations for graphics cards for stable Cascade and stable diffusion.

Stable Cascade is an amazing model from stability AI with requirements more challenging than stable diffusion.

A course for stable Cascade recommends 20 GB of vram, but it's possible to work with lower amounts under certain conditions.

Stable AI suggested 20 GB VRAM requirements for Cascade, but these can be lowered with smaller variants.

Community members have started producing their own third-party models for stable Cascade.

The RTX 360 12 GB is a recommended graphics card for processing larger models.

Maxon, a new company from China, offers a three-fan solution graphics card with decent feedback.

The 16 GB variant of the RTX 4060 is recommended for those who can afford a more powerful card.

MSI gaming cards feature three-fan variants with higher clock speeds and better cooling.

The RTX 4060 TI Super offers more powerful Cuda cores and larger memory bandwidth than the 4060 16 GB.

The MSI RTX 480 Super Gaming X Trio is a powerful and less expensive alternative to the 4080.

The RGX 490 is the top recommendation for a gaming card capable of handling stable diffusion and large models.

There is a new version of stable diffusion (stable diffusion 3) with models ranging from 800 million to 8 billion parameters.

For those interested in more powerful cards for training or inference, a video from November-December is recommended.

Hugging face provides stable Cascade files from stability AI with the largest ones being 14.4 GB.

The approach taken is to ensure higher quality than stable diffusion, avoiding less powerful models.

Some stable Cascade models can get very large, with one example being 34 GB for stage C.

Amazon offers a layaway scheme for purchasing graphics cards in installments.

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