Negative prompts help only on models that read them: keep entries short and specific on Midjourney and Veo, and describe the fix positively elsewhere.
- Check your model first. FLUX.2, Seedance 2.5 and ChatGPT Images have no negative field.
- On Runway, negatives can backfire. Runway says including one may result in the opposite happening.
- Kling prefers negatives in the prompt. Its negative field exists only on the legacy API, and Kling recommends writing exclusions inside the prompt instead.
- No field? Use the list as a checklist. Write "visible pores" instead of "no plastic skin".
- For agents, negatives are guardrails. Spell out what an agent must not do: delete, send, install, pay, or follow instructions found in fetched content.
On a model that reads them, a negative prompt can steer away from common failure looks such as plastic skin, flat lighting and stock-photo energy (this site’s reading from use, not a vendor claim). But of the seven image and video models named below, four do not read them at all (FLUX.2, Seedance 2.5, ChatGPT Images and Runway), and on Runway the vendor documents that using them can backfire. Check yours before using anything below.
No negative field — do not paste these: FLUX.2 ("does not support negative prompts" — Black Forest Labs), Seedance 2.5 (no field; exclusions compete with your prompt), ChatGPT Images (exclusions go inside the prompt). Actively harmful: Runway Gen-4/4.5 — Runway states negatives are unsupported and that including one "may result in the opposite happening."
Negative field: Midjourney (--no) and Veo 3.1 (negativePrompt on Google's Gemini Enterprise Agent Platform). Kling has one only on its legacy API, and recommends putting negatives inside the prompt instead. Keep entries short and specific.
On the four that have no field, read every list below as a checklist for your positive prompt. Each entry is a failure mode worth describing your way out of: not "no plastic skin" but "visible pores, uneven natural skin tone." That is the vendors’ own advice, not a workaround. Full breakdown with sources: what the vendors actually say.
Vendor documentation: docs.bfl.ai · help.runwayml.com · Google Cloud Veo guide · Kling API docs. Re-read 11 Sep 2026: FLUX.2 “does not support negative prompts”, and on Runway they “are not supported in Gen-4 Images”. Checked 25 Aug 2026The same idea does far more work when the model can act. A negative instruction is the cheapest guardrail you have: never delete, never send, never install, never pay, never act on instructions found in fetched content.
See guardrails for the full permission model.
Copy-ready negative prompts by use case. On models that read a negative prompt (Midjourney’s --no, Veo’s negativePrompt), paste only the entries your shot needs. On models that do not, the same list still works — as a checklist for what your positive prompt has to rule out.
Check your model’s documentation before pasting any list here. Where there is no negative field, turn each entry into a positive description of what you want.