Multiply sigmas

The dumbest, most effective sigma hack there is

Multiply sigmas from sigmas_tools_and_the_golden_scheduler does exactly one thing: takes a SIGMAS tensor, multiplies every entry by a factor, and hands it back. That's it. No curves, no formulas, no toggles. And yet it's arguably the most-reached-for node in the whole pack, because scaling a schedule is a shockingly useful move.

When you multiply a whole schedule by, say, 1.15, every step removes proportionally more noise than the sampler originally planned. The effect is a global "harder" render - stronger denoising at every point, which usually reads as more contrast and more pronounced detail, with a real risk of oversaturation if you push it. A factor under 1 does the reverse: a softer, gentler pass that's often the fix when an image comes out crunchy or overdone. Since the last sigma is always 0, multiplying keeps the endpoint pinned at zero - the schedule stays valid, the sampler keeps terminating properly.

Community wisdom picked up on this early. In a 2024 r/comfyui thread asking for a ComfyUI equivalent of the A1111 Detail Daemon, a commenter pointed straight at this node as "the same thing but in a more accurate way." That's generous - Detail Daemon sculpts individual steps while this moves the whole schedule at once, so you don't get the "leave the beginning and end alone" behavior. But as a global detail/strength knob you can drop inline without touching your KSampler settings, it's hard to beat.

What you set

Two inputs:

• sigmas - any SIGMAS tensor: from a built-in scheduler, one of this pack's schedulers, or a merged schedule
• factor - a float from 0 to 100, default 1 (i.e. no change)

One SIGMAS output, wired wherever your schedule was going next. Because it's just a multiplication, it composes with everything else in the pack: multiply a merged schedule, multiply a gradual merge, whatever.

Install & gotchas

ComfyUI Manager → search sigmas_tools_and_the_golden_scheduler, or:

cd ComfyUI/custom_nodes
git clone https://github.com/Extraltodeus/sigmas_tools_and_the_golden_scheduler

Restart, no model downloads. Pack-level gotcha applies: requirements.txt lists only asteval while the code imports matplotlib and scipy, so a minimal venv may need pip install matplotlib scipy asteval if the pack won't load. The factor box is a plain number input, so if you're doing A/B tests, treat it as a one-at-a-time experiment - there's no built-in preview, which is what the pack's Graph sigmas node is for.