Hello everyone. I've been conducting a thorough evaluation of the SDXL Turbo model for potential integration into a client's rapid prototyping workflow, and I've hit a consistent and puzzling roadblock during my technical assessment. While the first step of generation appears normal, the second step—without fail—degenerates into complete, garbled noise, rendering the output unusable.
I'm operating under a standardized testing framework to isolate variables. My setup and parameters are as follows:
* **Base Model:** `sd_xl_turbo_1.0_fp16.safetensors`
* **Inference Engine:** Automatic1111 WebUI (latest stable commit)
* **Sampler:** Euler a (as commonly recommended for Turbo models)
* **Sampling Steps:** 2 (aligning with the model's intended single-step/few-step design)
* **CFG Scale:** 1.0 (again, per the typical guidance for this architecture)
* **Dimensions:** 512x512
The workflow is simple: I input a basic prompt, and the first step shows a coherent, low-detail image forming. However, upon the second and final step, that image completely dissolves into colorful static. This occurs across multiple prompts and seeds.
My hypothesis is that this is a configuration conflict, likely between the model's expectations and the WebUI's pipeline. I've ruled out VRAM issues. My primary suspects are:
1. **Scheduler Incompatibility:** Is Euler a the correct choice here, or does SDXL Turbo require a specific, hardcoded scheduler that my setup is overriding?
2. **Parameter Poisoning:** Could there be a clash with a default WebUI setting (like a hidden "eta" or noise shift parameter) that is beneficial for standard models but catastrophic for the Turbo model's distilled timesteps?
3. **Preprocessing Misstep:** Does the model require a specific VAE or a fundamental preprocessing step that differs from standard SDXL?
I am approaching this from a vendor evaluation perspective: if this is a common pitfall, it significantly impacts the operational reliability score in my procurement playbook. Before I delve deeper into the code-level hooks, I wanted to consult the community's collective experience.
Has anyone successfully implemented SDXL Turbo in Automatic1111 and encountered this precise issue? What was the root cause and corrective action in your case? A structured breakdown of your working configuration would be immensely valuable for my comparative analysis.
null
Your issue is a known quirk with how some UIs handle the latent scheduling for these distilled models. You've correctly matched the low CFG and step count, but Automatic1111's default behavior on step 2 is likely applying noise that the model wasn't trained to handle. SDXL Turbo expects a very specific noise schedule for that second step.
Try this: add `--no-half-vae` to your launch arguments and regenerate. The FP16 VAE precision in some builds interacts poorly with the model's expected latent space during that final denoising step. I've seen this fix it more often than not.
If that doesn't work, bypass the UI's scheduler override entirely by generating via a script with a fixed seed and explicitly setting `scheduler='LCM'`. The Euler a recommendation is often wrong for the actual model card spec.
Yeah, the scheduler mismatch is huge here. I chased this same bug for a day. `--no-half-vae` is a good first test, but it didn't fix my specific case.
The key detail that got me was that `Euler a` in A1111 isn't the same as the `Euler Ancestral` scheduler the model card mentions. For a true apples-to-apples test, I had to use the Forge extension, which has a dedicated LCM scheduler option. Switching to that gave me clean 2-step outputs instantly.
So if the VAE flag doesn't work, the next step is definitely to bypass the default sampler list entirely. Great advice.
Integration Ian
Forge is the way. Can confirm that using its LCM scheduler option is the only reliable method I've found in the UI ecosystem. Euler a is fundamentally different, as you said.
One extra caveat: even with Forge, make sure you're on the very latest version. The LCM implementation there got fixed about three weeks ago. Older installs might still give you noise.