Best Negative Prompts for Stable Diffusion

Photo Editing Updated August 29, 2026 by GenPrompto
Prompt
(negative prompt) low quality, blurry, deformed, extra limbs, extra fingers, missing fingers, mutated hands, poorly drawn face, disfigured, bad anatomy, watermark, text, signature, cropped, out of frame, jpeg artifacts, worst quality -- pair this with your positive prompt to reduce these specific common defects.

What this does

A reusable negative prompt for Stable Diffusion -- targets extra fingers, warped faces, and quality artifacts specifically.

A negative prompt tells Stable Diffusion what to avoid, and it only works when it names specific defects — a vague “bad quality” negative prompt does little, while listing the actual artifacts you’re seeing (extra fingers, warped faces, blurry backgrounds) meaningfully reduces them.

What this produces

A reusable negative prompt targeting common Stable Diffusion artifacts — anatomy errors, quality issues, unwanted style elements — to pair with your positive prompt and reduce specific defects in the output.

Variations

Two ready-to-copy versions for different use cases.

General Quality Base Version
(negative prompt) low quality, blurry, deformed, extra limbs, extra fingers, missing fingers, mutated hands, poorly drawn face, disfigured, bad anatomy, watermark, text, signature, cropped, out of frame
Portrait-Specific Version
(negative prompt) deformed face, asymmetrical eyes, extra fingers, mutated hands, bad hands, poorly drawn hands, blurry, low resolution, cross-eyed, disfigured, ugly, duplicate, watermark, text. Use this alongside your main positive prompt specifically for portrait generations, where hands and facial symmetry are the most common failure points.

Who this is for

Stable Diffusion users whose images come out with extra fingers, warped faces, or blurry backgrounds — common artifacts a good negative prompt directly reduces.

Example Output

Listing specific artifact terms (extra limbs, deformed hands, low quality, blurry) tells the model exactly what to steer away from — a bare “bad quality” negative prompt is too vague to meaningfully reduce any specific defect.

Tips for better results

  • Target the specific defects you’re actually seeing — if hands are the problem, prioritize hand-related negative terms over a generic list.
  • Keep a reusable base negative prompt for quality issues, and add scene-specific terms as needed.
  • Don’t over-stuff the negative prompt — an excessively long list can dilute the effect of the terms that actually matter.
  • Adjust CFG scale alongside your negative prompt if defects persist — the two work together, not independently.

What didn’t work as well

Using a single vague term like “bad quality” as the entire negative prompt. It’s too unspecific to meaningfully reduce any particular defect — listing the actual artifacts you’re seeing (extra fingers, warped faces, blurry backgrounds) is what a negative prompt is built to target.

Pair this with ChatGPT Prompt for Christmas Photo, or explore ChatGPT Prompts for Pictures of Yourself if you’re looking for something related.

FAQ

Do negative prompts work the same across all Stable Diffusion versions?

Effectiveness varies somewhat between SD1.5, SDXL, and newer versions — if a term seems to have no effect, check whether your specific model version and interface support negative prompt weighting.

Can I use too many negative terms?

Yes — an excessively long list can dilute the weight of the terms that matter most. Start with the base version and add only what addresses artifacts you’re actually seeing.

Does a negative prompt work the same in Midjourney or DALL-E?

No — negative prompting syntax and support vary significantly by tool; this specific approach is built for Stable Diffusion’s interface.

Related