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Stable Diffusion XL 1.0: prompts, settings and what it still does best

Argomento: Modelli
Di Captain
Pubblicato il 2026-10-01
How to get the most out of the official SDXL 1.0 base model: native resolutions, CFG and sampler settings, the refiner, negative prompts and ideas for styles where SDXL still shines.
Questa pagina non è ancora tradotta, quindi è mostrata in inglese.

Panoramica

Stable Diffusion XL
1.0 is Stability AI's 2023 flagship latent diffusion model. It uses two text encoders (OpenCLIP ViT-G and CLIP ViT-L), generates natively at 1024x1024 and ships with an optional refiner that polishes the final denoising steps. It remains the parent of the largest fine-tune ecosystem in the catalog:
Pony
, Illustrious, NoobAI and thousands of realistic checkpoints all descend from it.
The base model itself has a soft, painterly tendency and a broad knowledge of art styles. It is less literal than
Flux
, which makes it good at loose, atmospheric images and quick style exploration.

Riferimento

Nome
Tipo
Cos'è
Prompt
text
Comma-separated phrases or short sentences. Quality words (highly detailed, sharp focus) still help on the base model.
Negative prompt
text
blurry, lowres, watermark, text, deformed hands. Keep it short.
CFG
5-8
7 is the classic value. Lower for painterly looks, higher for literal prompts.
Steps
25-40
30 with DPM++ 2M Karras is a reliable default.
Resolution
1 MP
1024x1024, 1152x896, 896x1152, 1216x832, 832x1216, 1344x768, 768x1344.
AD
Nessuna installazione: esegui i modelli IA nel cloud
BitVector Prism è il modo più semplice per iniziare: scegli un modello, scrivi un prompt e genera in una web app pulita, senza configurare nulla. BitVector è disponibile anche su Discord e sul web (SpyGlass).

Passo dopo passo

  1. Start at 1024x1024,
    CFG
    7, 30 steps, DPM++ 2M Karras.
  2. Put the subject first, then style, then lighting and composition words.
  3. Add a short
    negative prompt
    and keep it stable while you iterate on the positive.
  4. If a face or hands look off, run a second
    img2img
    pass at 0.3-0.4 denoise or use the refiner for the last 20 percent of steps.
  5. Switch to a non-square bucket (1216x832 for landscapes) once the subject is right.

Esempi

Painterly landscape

a vast misty fjord at dawn, tiny red fishing boat, oil painting, impasto brushwork, soft pink and slate palette, wide composition
Negative: blurry, lowres, watermark, text

Concept art

concept art of a nomad caravan crossing a salt flat, giant tortoise carrying a wooden house, dramatic clouds, matte painting style, cinematic lighting, highly detailed

Creative idea: paper diorama

a layered paper-cut diorama of a night market, warm lanterns made of tissue paper, miniature paper people, macro photography, shallow depth of field

Consigli

  • SDXL responds strongly to artist and medium names. Two or three style words do more than ten adjectives.
  • Do not generate below 1024 on the long edge; the base model falls apart under 768.
  • Prompt weights like (word:1.2) work here, unlike on Flux.
  • If you want realism, a dedicated realistic SDXL
    checkpoint
    from this catalog will beat the base model; use the base for painterly and conceptual work.

Risoluzione dei problemi

Faces are mushy at 1024

Perché succede
The base model has limited face detail compared with fine-tunes.

Come risolverlo
Use the refiner or an img2img pass at 0.35 denoise, or inpaint the face at a higher effective resolution.

Prompt is ignored in favor of a generic style

Perché succede
CFG too low or too many competing style words.

Come risolverlo
Raise CFG to 8 and cut the style list to two or three terms.

AD
PirateDiffusion
Nessuna installazione: esegui i modelli IA nel cloud
PirateDiffusion è solo su Telegram ed è pensato per i professionisti: migliaia di modelli, LoRA e workflow tramite comandi in chat, con generazione illimitata a prezzo fisso.

Domande

Do I need the refiner?

No. The base model works alone. The refiner adds micro detail on the last steps and is most useful for photographic prompts.

Can I use SD 1.5 LoRAs and embeddings?

No. SDXL has a different architecture; use
LoRAs
and embeddings trained for SDXL.

Link e fonti

Modelli di questa guida

Scritto da
Captain

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