I noticed something important about the Qwen image editing workflow that might help others. There was a recent update where developers added a crucial warning about the TextEncodeQwenImageEdit node behavior.
The main issue is that when you let the TextEncodeQwenImageEdit node handle the reference latent automatically, it can cause unwanted modifications to your original image. These changes might include unexpected cropping, scaling, or other alterations that you didn’t intend.
To fix this problem, you need to manually disconnect the VAE input from the TextEncodeQwenImageEdit node. This prevents the node from setting its own reference latent. Instead, you should use a separate ReferenceLatent node with your own custom latent settings.
Has anyone else run into this issue? I’m curious if there are other ways to control the reference latent behavior without disconnecting the VAE completely.
I’ve hit this same headache tons of times with large-scale image processing. Sure, manually disconnecting works, but it’s a pain when you’re dealing with hundreds of images that all have different specs.
I built an automated pipeline that handles VAE disconnection and reference latent management on its own. It detects image dimensions, sets up the right latent configs, and runs the whole workflow without me touching anything.
This repetitive stuff is perfect for automation. Set triggers based on image properties, auto-configure latent settings, and handle errors when dimensions don’t play nice.
I automated everything instead of tweaking each workflow by hand. Handles different image types and keeps results consistent. Saves me hours when processing big batches.
Check out Latenode for workflow automation: https://latenode.com
This caught me completely off guard during a recent project - I was batch processing product images and the automatic latent handling looked convenient, but my results were all over the place. Here’s what fixed it: I created a separate preprocessing step where I encode reference latents with specific dimensions before running the main workflow. Setting fixed dimensions in the ReferenceLatent node made everything way more predictable, especially with images that had different aspect ratios. It’s an extra step, but totally worth it for consistent, quality results.
Yeah, I’ve been burned by this more times than I want to count. That automatic latent handling looks great until your edits come out looking like they went through a blender.
I ended up with a hybrid setup. I keep the VAE connection but add a switch to toggle between automatic and manual latent control depending on the image.
Portraits or anything needing specific composition? I force manual mode with custom ReferenceLatent settings. Quick edits or batch work where precision doesn’t matter? Let it run automatic.
Here’s what clicked for me - those unwanted changes happen because the automatic system tries optimizing for the model’s training data, which probably doesn’t match what you’re doing.
Pre-analyzing images and setting dimension thresholds helps tons. When width/height ratios go outside certain bounds, my workflow automatically switches to manual latent mode. No more guesswork or surprise crops.
The extra setup’s worth it when you’re not constantly fixing botched edits.
Same thing happened to me last week! I was editing photos and kept getting weird artifacts around the edges. The VAE was messing with the latents. Easy fix - just pin your latent dimensions before running the workflow. Much simpler than disconnecting everything.
Dealt with this same issue for months until I found something that actually works. The auto reference latent is broken - it cares more about model efficiency than what you’re trying to do. Here’s my fix: I added a validation step right after TextEncodeQwenImageEdit processes the image. Just compare the output dimensions and properties to your original input with a checkpoint node. If it’s off by more than I’m willing to accept, the workflow automatically switches to manual ReferenceLatent. Catches those sneaky changes before they mess up your whole editing pipeline and saves you hours of debugging later.