Auditing LoRAs At Maximum-Safe Weights (See What They Really Do)
**Category:** checkpoint | **Tier:** Insider ($5) | **Estimated reading time:** 6 min
**Excerpt:** When you're triaging which LoRAs...
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The 10% Accent Rule: Composites That Beat Their Ingredients
You ran a graft-comparison round at 30%. One candidate placed surprisingly high in a small early eval, then collapsed when you verified with more prompts — but the model has a real visual character you don't want to lose. Most people drop it and pick from the remaining survivors. The better move: keep it as a 10% accent on top of the survivors. The composite usually beats every ingredient including itself at 30%. Here's the rule, when it applies, and why a primary-secondary-accent split at roughly 70/20/10 is the structure that works.
Why Baked LoRAs Behave Differently Than Runtime LoRAs
You tested a LoRA stack at runtime — included it in the prompt at specific weights — and the output was great. You baked the same stack into the model at the same weights, expecting the same output. Instead you got neon nightmare, blown-out colors, or just a noticeably weaker version of what worked at runtime. Same weights, same LoRAs, same base model. Why does the bake behave differently? Three reasons that compound: CFG amplification math, fp16 precision drift, and sequential layering effects. Understanding each tells you why some recipes will never bake, no matter how much you tune.
Why Some LoRAs Survive Baking And Others Don't (Passive vs Trigger-Dependent)
You baked your favorite LoRA recipe into a checkpoint following all the right steps. The runtime version of the recipe produces beautiful images. The baked version produces something flatter, weaker, like the LoRAs are barely there. The math is right. The weights match. The fault isn't in your bake — it's in the type of LoRA you baked. Passive style LoRAs translate cleanly to baked weights; trigger-dependent LoRAs don't. Here's the distinction, why it matters, and how to know which kind you're baking before you find out the hard way.