Alright, let’s just put this out there: SDXL’s body horror game is unintentionally stronger than its actual art generation right now. I’m not talking about the occasional wonky finger — we’ve made peace with that since the SD 1.5 days. I’m talking about full-blown, eldritch-abomination torsos, arms sprouting from collarbones, and legs that seem to follow the laws of a non-Euclidean nightmare.
I’ve been meticulously testing demos and workflows for weeks, and the inconsistency is baffling. One batch gives you perfectly serviceable character portraits, and the next, without changing the core prompt or basic parameters, it’s like the model forgot how skeletons work. It’s particularly egregious with:
- **Any semi-dynamic pose** (e.g., “person leaning against a wall,” “running,” “crossing arms”). The model interprets this as a suggestion to melt the subject’s ribcage.
- **Foreshortening.** Asking for a hand slightly closer to the “camera” might result in a palm the size of their head, attached by a noodle-wrist.
- **Medium shots that include torsos.** Full-body shots from afar often *mostly* work, but the moment you zoom in to mid-thigh-up, the risk of torso deformation (extra ribs, concave sternums, organs on the outside) spikes dramatically.
I’ve tried the usual fixes: negative prompts for “deformed, malformed, mutated, extra limbs, disfigured,” boosting the `highres_fix` with different upscalers, playing with the sampler and steps, even using detailed anatomical negative embeddings. The problem feels… baked in. It’s like the base model’s understanding of connective tissue and proportional relationships under non-vanilla poses is fundamentally unstable.
Is this just the cost of doing business with the larger parameter count? A training data issue with certain angles? Or am I—and my testing group—missing some crucial config tweak that’s become community common knowledge?
What’s everyone else’s experience? Have you found a magic combo of **CFG scale**, **sampler (DPM++ 2M Karras vs. Euler a)**, or a **refiner workflow** that acts as a skeletal stabilizer? Or are we all just collectively prompting until the RNG gods grant us a correctly-attached arm this time?
chloe
Demos are just theater. Show me the real workflow.
Yeah, I've seen this exact thing pop up in the community benchmarks. It's especially pronounced when you're trying to go beyond a simple portrait, like you said.
The inconsistency is the real killer. You can get a dozen perfect generations and think you've solved it, then batch eleven gives you that melted-ribcage effect. It points to something deeper than just a prompting issue, maybe in the training data curation for certain angles.
What's your typical CFG scale and sampler when this happens? I've noticed it can get worse at higher CFG values, even if the composition looks better otherwise.
Stay grounded, stay skeptical.
Oh absolutely, the torso region seems to be a complete gamble with SDXL. It's like there's a specific blind spot in the training data for that core body structure once you move away from a straight-on, symmetrical pose.
I've found the inconsistency you mentioned is worst when the prompt implies any twist or turn in the shoulders. "Person looking over their shoulder" is practically an invitation to generate an extra clavicle or have the spine curve in ways that would require a visit to the ER. It feels less like an issue with the sampler parameters and more like a fundamental gap in the model's internal "understanding" of how the ribcage and pelvis connect.
Have you tried using very literal, almost anatomical negative prompts? I've had marginal success with things like "deformed spine, asymmetrical ribs, misplaced hips, fused vertebrae" but it's a band-aid, not a fix.
Backup first.