**"Turbo or base CFG?"** Turbo. CFG 1.0, 8 steps.

**"Why does my negative prompt do nothing?"** Because CFG is 1.0. Negative
prompts require classifier-free guidance, which a distilled model doesn't run.
This isn't a bug and there's no setting to change.

**"Can I use my Illustrious/Pony prompts?"** Not directly. Rewrite them as
sentences. Booru tags are a vocabulary this model was never trained on.

**"Why is it slow?"** Cost scales with total tokens, and text and image share
one attention sequence. 832×1216 is roughly 2x the cost of 624×912.

**CFG 1.0. Not 3.5, not 7.** This is guidance-distilled. Raising CFG does not
make it follow the prompt harder — it runs the transformer twice per step
(so ~2x the time) and blows out contrast. If your images look burnt or
over-saturated, CFG is the first thing to check.

| setting | value |
|---|---|
| **CFG** | **1.0** |
| **Steps** | **8** (4–8 all work; 8 is the sweet spot) |
| **Sampler** | Euler — flow-matching (`FlowMatchEulerDiscreteScheduler`) |
| **Scheduler / sigmas** | linear / normal |
| **Shift** | 3.1582 (Krea 2's own default — leave it alone) |
| **Negative prompt** | **does nothing.** Inert at CFG 1.0. Don't bother writing one. |
| **Resolution** | 832×1216, 1216×832, or 1024×1024 |

There is only one sampler for this architecture. Krea 2 is a rectified-flow
model — Euler a, DPM++ 2M, UniPC and friends solve a different equation and
simply aren't options. If your UI shows a sampler list, pick Euler.

**On the sigma scheduler:** I ran a blind 4-way test (linear / karras /
exponential / beta, two seeds). The curves measurably differ but the difference
is not visible — blind rankings came out anti-correlated between seeds. Use
linear and don't think about it again.