RTX 4090 Users Sound Off | Is Krea 2 LoRA Training Unacceptably Slow?
Edited By
Dr. Emily Chen
A growing number of users are expressing frustration over sluggish training times when using Krea 2 on RTX 4090 graphics cards. With claims that training should only take a mere five seconds per step, many feel stuck waiting far longer, prompting questions about potential causes for the delays.
Slow Training Times Stir Controversy
Users are baffled as they report extremely long training times for LoRA models. One user shared, "I'm getting these crazy long timers every time" while using a card that is generally touted for its speed.
Many commenters chimed in, sharing their experiences and tips.
"Power draw is low and memory is at 97%," a user speculated. "Are you sure you aren't hitting memory allocation issues?" This highlights potential hardware limits that could hinder performance.
Key Insights and User Suggestions
Feedback points to several factors that may contribute to these slowdowns:
Memory Management: Adjusting the
blocks_to_swapconfiguration might alleviate bottlenecks. "I fed your feedback to Gemini it made me add this line and it changed everything!" stated one respondent.Dataset Optimization: Suggestions included normalizing image resolution. Users noted that limiting to 1024x1024 or 720 resolution could speed up training times.
Recommended Tools: Some users suggested alternatives like Fizgig, praised for its ease of use and effective documentation. "I've done literally 5 LoRAs on it it literally takes 45 minutes to do a LoRA," noted an advocate.
Notable Quotes from the Community
"I love Kohyaa but Krea 2 doesn’t have good support in Musubi Tuner," a user remarked, emphasizing the need for better tools.
Interestingly, some users reported faster training stats, with one stating, "I see around 2.5 sec/it on my 4090 training Krea 2." Clearly, results vary significantly.
Sentiment Patterns and Community Response
The user community offers mixed views: while some share productive, practical solutions, others are deeply frustrated by the slow speeds.
Users are now questioning whether adjustments to their setups can improve efficiency. How long until a permanent fix rolls out?
Key Highlights
▽ Users report training times exceeding expectations drastically, leading to growing frustrations.
✅ Many recommend optimizing memory settings and image resolutions for improved performance.
📊 "Running it in the cloud using VNC is too slow; I built a normal web interface instead," shared one user, suggesting a need for easier solutions.
With ongoing issues in training efficiency, it raises the question: what will it take to accelerate LoRA training on high-end GPUs like the RTX 4090?
What’s Next in the Graphics Training Game?
There’s a strong chance that software updates from developers will address the speed issues seen in Krea 2 training on RTX 4090 GPUs. With the community actively sharing insights and potential improvements, it’s likely that within the next few months, enhancements will roll out to optimize memory management and speed up LoRA model training. Experts estimate that if developers take note from user feedback, training times could eventually drop closer to the expectation of five seconds per step, with a high probability of smoother performance experienced by most users—perhaps up to 80% of the community reporting better throughput after these updates.
Connecting Dots with the 1970s Oil Crisis
An interesting parallel can be drawn between the current frustrations with slow GPU training and the oil crisis of the 1970s. Just as the oil industry struggled with supply chain inefficiencies and rapid demand increases, causing major frustration for consumers, the tech community now faces bottlenecks in performance that hinder progress. In both cases, stakeholders—whether they be oil companies or software developers—must find practical solutions amid rising pressures. Just as resource management strategies evolved in the wake of that crisis, we may soon see similar innovative tools and methods reshaping how LoRA training is approached, leading to greater efficiency and transformation in the tech space.