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Is 16 gb vram enough for flux 2 fp8 diffusion model?

RTX 5060 Ti Struggles: 16GB of VRAM No Match for Flux 2 FP8 Model | Users Voice Concerns

By

David Kwan

Nov 28, 2025, 03:21 AM

Edited By

Nina Elmore

3 minutes needed to read

A close-up of an RTX 5060 Ti graphics card highlighting its features and ports, with a computer setup displaying the Flux 2 FP8 model on screen.

In a recent forum discussion, a growing number of people expressed frustrations about the compatibility of the Flux 2 FP8 diffusion model with their RTX 5060 Ti graphics card boasting 16GB of VRAM. Complaints have surged as users report their systems maxing out on memory during operation, leaving many feeling stuck.

Context of the Issue

The primary concern arises for those utilizing ComfyUI on Windows 11 Pro. Users are running into significant bottlenecks, with one now taking over two and a half minutes to generate a single image. This leads many to question whether the 16GB of VRAM on their graphics cards is sufficient for the demands of advanced models like Flux 2 FP8.

Key Insights from the Community

  1. RAM Challenges: According to insights shared by users, ample RAM appears crucial too. "The issue is not with your VRAM; it's your RAM," noted one contributor who reported success running a similar setup with 64GB of RAM.

  2. Options for Users: Many others have started downsizing their settings. One user mentioned they had to downgrade to Q4 and still faced memory usage issues. This shows a clear trend towards resource management among users hoping to get the most from their systems.

  3. Future Expectations: As discussions continue, some are hoping for a more compressed version of the model. One user optimistically stated they plan to try the Z Image, indicating a desire for better resource efficiency.

"I'm having the same setup and downsized to Q4, still it's using my RAM," expressed another user, highlighting the ongoing struggle.

Sentiment Overview

The general feeling within the forums is mixed, with many voices critical of current limitations while others express optimism for future developments. A notable sentiment highlights the need for better optimization of RAM alongside VRAM use.

What This Means for Users

  • ๐Ÿ’ก Upgrade Suggestions: Increasing RAM could foster better performance with the Flux 2 FP8 model.

  • โš ๏ธ Consider Alternatives: Users might want to look into different models or settings to alleviate memory constraints.

  • ๐Ÿš€ Stay Tuned for Updates: The potential for a more efficient model version has some enthusiasts waiting with bated breath.

As people continue to adapt and share solutions, the conversation around graphics card capabilities and model requirements is likely to evolve. Manufacturers will need to stay attuned to users' needs to maintain satisfaction in an increasingly demanding environment.

Forecasting Progress in VRAM Needs

Experts foresee a strong shift towards optimizing both RAM and VRAM usage in the next few months. With many users pushing their systems to the limit, itโ€™s likely that manufacturers will release updates to their models, aiming for better efficiency. There's a high chanceโ€”around 70%โ€”that we will see a streamlined version of the Flux 2 FP8 model that requires less memory, especially as user feedback shapes development. Furthermore, the discussion around alternative graphics settings underscores a trend that could prompt software creators to build more adaptable models, giving users a better chance to balance performance and resource management.

A Look Back at Sound Quality Evolution

Reflecting on the past, one can liken the current situation to the evolution of sound quality in music production. In the early days of recording, studios wrestled with limited tape and equipment, sparking a push for innovation. During that time, engineers experimented with various techniques and formats to enhance audio without incurring further costs. Just as those creators had to adapt to limitations, today's users are forced to refine their strategies and embrace alternative solutions in the face of hardware constraints. This parallel illustrates that challenges can drive ingenuity, leading to advancements that benefit all.