Fix LTX 2.3 Audio Issues in 2026: Proven ComfyUI Workflow Tweaks to Eliminate Metallic Hiss

Fix LTX 2.3 Audio Issues in 2026: Proven ComfyUI Workflow Tweaks to Eliminate Metallic Hiss

Audio artifacts in LTX 2.3 have long plagued users of Stable Diffusion audio generation tools, with metallic hiss and unnatural tonal distortions undermining the quality of generated soundscapes. Now, a community-verified fix shared on Reddit has emerged as the go-to solution for improving audio fidelity — all without new models or retraining. By adjusting just two key components in your ComfyUI workflow — the scheduler and sampling steps — you can transform noisy outputs into clean, natural-sounding audio.

Step 1: Replace LTXV Scheduler with BasicScheduler

For both the full development and distilled versions of LTX 2.3, the first critical fix is swapping the proprietary LTXV scheduler with the standard BasicScheduler. According to u/Mountain_Platform300, whose Reddit post sparked this breakthrough, this single change reduces high-frequency noise by up to 70% and improves temporal coherence. Users report that the audio loses its synthetic, "robotic" quality and gains a more organic, analog-like texture. This works because BasicScheduler distributes noise reduction more evenly across sampling steps, unlike LTXV’s aggressive early-stage denoising that amplifies artifacts.

Step 2: Optimize Sampling for Distilled Models

The distilled model alone struggles with rich sound generation, but pairing it with the full dev model in a two-phase workflow yields exceptional results. Start with the first four sampling steps using the full dev model at CFG 3.0, with a distilled LoRA applied at 0.2 strength. Then switch to the distilled model alone for the final four steps, lowering CFG to 1.0. This hybrid approach leverages the dev model’s expressive power early on, while the distilled model cleans up residual noise without introducing new artifacts. Community testers confirm this method consistently eliminates metallic hiss across vocal and ambient prompts.

Step 3: Configure KSamplerSelect for Res_2s

Don’t overlook the sampler node. Replace the default ClownsharKSampler with KSamplerSelect and set the resolution preset to "res_2s." This setting aligns sampling resolution with LTX 2.3’s native audio frame structure, reducing aliasing and phase distortion. Users who skipped this step reported partial improvement — only those who combined BasicScheduler, two-phase sampling, and res_2s achieved full artifact elimination.

Why This Works: The Science Behind Audio Artifacts

While LTXV’s scheduler was designed for speed, its aggressive noise removal disrupts the natural harmonic progression of audio signals. BasicScheduler, by contrast, preserves low-energy frequencies that carry timbral detail. Meanwhile, the distilled model’s lower parameter count makes it sensitive to early-stage noise — hence the need to pre-process with the full model. Together, these adjustments compensate for the distilled model’s limitations while maintaining computational efficiency.

Download the Tested ComfyUI Workflow

The complete node configuration — including all scheduler, sampler, and LoRA settings — is available via the original Reddit thread here. A visual diagram of the workflow is included below.

For deeper insights into ComfyUI node configuration, see our ComfyUI Beginner Guide. Official documentation for Stable Diffusion audio models is available on the Stability AI GitHub, and ComfyUI’s core nodes are documented here.