Midjourney Not Following Prompts: How to Fix Ignored Words

If Midjourney is suddenly ignoring specific words in your prompt, rendering the wrong styles, or completely omitting key details, you are dealing with "prompt drift" or token dilution. Unlike conversational AI models, Midjourney parses prompts as a collection of tokens rather than understanding natural grammatical context. When your outputs do not match your text inputs, it is usually due to poor prompt structure, conflicting parameters, or the model prioritizing certain tokens over others.

Follow these structured troubleshooting steps to force Midjourney to recognize ignored prompt elements and restore output accuracy.

1. Switch or Verify Your Model Version Midjourney updates its default models regularly. If you recently noticed a sudden drop in prompt adherence, your settings might have reverted to an older version, or a new version (like V6) is interpreting your prompt differently than V5.2 did.

1. Open Discord or the Midjourney web interface.
2. Type /settings in the message box and press Enter.
3. Look at the active model version in the settings panel. If it is set to an older version, click the button for the latest model (e.g., Midjourney Model V6).
4. Alternatively, manually force the model by adding the version parameter to the very end of your prompt, such as --v 6 or --v 5.2.

*Note: V6 is much more sensitive to literal text and grammatical prompts, while V5.2 relies more on short, comma-separated keywords.*

2. Use Multi-Prompts to Adjust Word Weights If Midjourney is ignoring a specific object or color in your prompt, it is likely because the model's neural network assigns more "weight" to other words in the sentence. You can manually assign importance using double colons (`::`).

1. Break your prompt into distinct concepts using ::. 2. Add a numerical weight immediately after the colons. If no number is specified, the default weight is 1. 3. For example, if you prompt red cup on a wooden table and the cup keeps turning blue or white, rewrite it as: red cup::2 on a wooden table::1 4. To make a neglected element even more prominent, increase its weight relative to the rest of the prompt (e.g., red cup::3 on a wooden table::0.5). Ensure the overall math remains balanced so you do not distort the final image composition.

3. Replace Negative Words with the `--no` Parameter Midjourney struggles with negative phrases like "no trees," "without cars," or "avoid red." The model sees the words "trees," "cars," and "red" and actually *adds* them to the canvas because it does not understand negative English syntax.

1. Identify any negative phrasing in your prompt text and remove it entirely. 2. Go to the end of your prompt. 3. Add the --no parameter followed by the elements you want to exclude. 4. For example, instead of writing a park with no people, use: a park --no people 5. If you want to exclude multiple elements, separate them with spaces or commas after a single --no command: a sunny park --no people cars buildings

4. Reduce Stylize and Chaos Settings High stylize (`--s`) and chaos (`--c`) values give Midjourney more artistic freedom, which frequently causes it to deviate from your literal text prompt to create a more "beautiful" or "unpredictable" image.

1. Check your prompt for the --stylize or --s parameter. The default is 100. If you have it set to 250 or higher, it will prioritize aesthetic quality over prompt accuracy.
2. Lower the stylize value by adding --s 50 or even --s 0 to your prompt.
3. Check for the --chaos or --c parameter. This parameter controls how varied the initial grid results are. Reduce this to --c 0 to prevent the model from generating wild, off-prompt variations.

5. Reorganize Your Prompt Structure (Token Order) Midjourney reads prompts from left to right. Words placed at the very beginning of the prompt carry significantly more weight than words placed at the end.

1. Move the most critical subject of your image to the first 3 to 5 words of your prompt.
2. Move background details, lighting styles, and medium descriptions (e.g., "oil painting", "3D render") to the middle or end of the prompt.
3. Keep your overall prompt under 60 words. Extremely long prompts cause "token dilution," where the model simply forgets or drops words near the end due to context limitations.

When to Escalate If Midjourney continues to ignore basic parameters, fails to process `--no` commands entirely, or generates completely random images unrelated to your prompt, there may be an active bug in the model pipeline. Check the **#status** channel in the official Midjourney Discord server to see if the engineering team has reported a temporary model regression or database degradation. If no outage is active, you can report the behavior in the **#member-support** channel.