PSA: Krea 2 variance is easy in ComfyUI (no LoRA-s or custom nodes needed)

There are quite often posts here complaining that Krea 2 is too predictable / different seeds give almost the same output / you need to type in extremely long prompts to get good images / there is no surprise factor any more since you get exactly what you typed in. Well - actually there is a very easy solution for that - use the text encoder model as LLM to do prompt expansion (PE). Here I'm showing one possible workflow for doing that. Funnyly enough I'm actually using the Qwen 2.1 PE system prompt here - I really don't care what it's "meant for" - works well enough for me. I added as an example 5 images - these are first 5 random (not cherrypicked) results that I got with this simple prompt: Candid mobile phone photo. Young woman wearing party dress. Evening dorm party in simple dormroom. Full size images with metadata No LoRA-s, no messing with model specific custom nodes. For me this is quite enough variance. Plus now you have two nobs to control that - PE seed to give you extreme changes and sampler seed to give you more fine grained changes. Here is the link for the workflow Hey, you promised no custom nodes, but there are some in this workflow! Yeah, I use some for convenience, but they have nothing to do with the prompt expansion itself. If you are curious then this is why they are in there: - rgthree-comfy - I like the seed control node. This could just be built in "Seed" node - comfyui-easy-use - their "If else" node is good for turning PE on and off. Purely convenience - comfyui-custom-scripts - their "Show Text 🐍" node actually saves the expaneded prompt to image metadata (as opposed to built in nodes that just show it but don't save it). Again - purely convenience. - RES4LYF - their "ClownsharKSampler" is what I use mostly with Krea 2. Could be just built in "KSampler" with whatever sampler / scheduler combo you prefer. Q&A: Q: OMG, it makes generation slower!! A: It adds some time to the creation. On my 5070Ti I can create a 3MP image with int8 model and 8 steps in ~18s. PE adds ~4s to that (depends on how long is your manual prompt, how much additional text it generates etc.) For me those 4s are not an issue. Q: My disk is slow / I don't have much RAM or VRAM - more model loads and unloads???? A: It is the same text encoder model that would have to be loaded anyway any time you change the prompt. So once PE is ready the text encoding step runs extra fast as the model is already in VRAM. Q: Won't such a crappy LLM model hallucinate? The expanded prompt is for sure weird and inconsistent? A: Who cares! Do you read the whole reasoning output of LLM models? Why should you care about the internals if the images you get are more varied and surprising? But you certainly can take the prompts that created good images and tweak them manually. Q: Do I need to use abliterated / heretic / uncensored versions of the text encoder now? A: Normal Qwen3VL 4B does not seem to care much about the topics when it is running as text generator. Like surprisingly little. So before starting to use alternative models (which mess with the quality of the final image when used as text encoder) do try just the normal one. Q: The official ComfyUI template already has PE, why post this? A: Just a reminder that this option exists :) And that you can use whatever system prompts there - no need to stick with the "official" or "correct" one. If the goal is variance and surprise then you can't really go wrong with any system prompt that targets image generation. Heck - even prompts for creating Ideogram or Ming Image JSON could be interesting. submitted by /u/prookyon [link] [comments]

Source: r/StableDiffusion | 2026-10-03

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