When an AI image comes out distorted, blurry, or nothing like what you asked for, the fix usually depends on which kind of failure you are seeing. A prompt that ignores your instructions needs different treatment from a sharp image with mangled hands. This guide helps you identify the problem, make the most effective change first, and check whether it worked. For a related guide, see Keyboard Typing Wrong Characters? How to Fix Keyboard Language and Layout Settings. For a related guide, see AI Citations Are Wrong or Missing? How to Verify and Fix Them.
"Alignment" can mean two things here: whether the image matches your prompt, and whether elements are arranged correctly (centered subjects, straight text, sensible layout). Both are covered below.
Step 1: Name the problem before changing anything
Changing the prompt, settings, and tool all at once makes it impossible to know what helped. Match your result to one of these:
- Ignores instructions: missing objects, wrong colors, wrong number of people, wrong style.
- Anatomy or object errors: extra fingers, warped faces, merged objects, impossible geometry.
- Garbled or misplaced text: misspelled words, nonsense letters, text in the wrong spot.
- Soft, noisy, or low-detail: blur, grain, smeared textures, a plastic look.
- Composition problems: subject cropped, off-center, wrong aspect ratio, repeated or stretched subjects.
Generate a few variations first. If one in four looks right, you have a reliability problem that small prompt changes can fix. If none are close, the prompt or the tool's capabilities are the issue.
Step 2: Fix the prompt first (it is free and reversible)
Most "wrong" images come from prompts that are vague, overloaded, or contradictory. Try these in order:
- Lead with the subject and action. Say what the image is of before describing style. "A ceramic coffee mug on a wooden desk, morning window light" works better than a list of mood words.
- Cut it down. Prompts with many subjects, each with its own attributes, often leak details between them (the red hat ends up on the wrong person). Generate the core scene first, then add details through editing.
- Remove contradictions. "Minimalist" with "highly detailed intricate patterns," or "photorealistic" with "watercolor," pulls the output in two directions.
- Be specific about what matters. Name the camera angle (close-up, overhead, wide shot), framing, lighting, and background rather than hoping the model picks them.
- State positions plainly. "On the left… on the right…" helps, though no tool follows spatial instructions perfectly.
Template: [Subject + action], [setting], [camera angle and framing], [lighting], [style or medium]. Avoid: [one or two specific things you don't want].
Check: run the revised prompt several times. If the key element appears most of the time, the prompt was the problem. If it still gets ignored, go to Step 3.
Step 3: Check settings and technical limits
Available controls vary by tool and version, so check the official documentation for the one you use. Chat-based generators offer few settings, so rely on prompting and editing instead. Tools with more controls are worth tuning:
- Aspect ratio and resolution. Subjects get cropped or duplicated when the canvas shape suits the scene poorly. In Midjourney, the
--arparameter sets aspect ratio (for example--ar 3:2). In Stable Diffusion-based tools, generating far above the model's native resolution often causes repeated or stretched subjects. Generate near the native size, then upscale. - Prompt-adherence setting (CFG scale in Stable Diffusion tools). Too low and the model drifts from your prompt; too high and images can look oversaturated or harsh. Adjust in small steps rather than jumping to extremes.
- Steps and sampler. Very low step counts can leave images unfinished or noisy. Raising steps helps only up to a point, so don't assume more is better.
- Stylization (
--stylizein Midjourney). Higher values favor the model's aesthetic over literal prompt-following. Lower it if your instructions are being overridden. - Negative prompts. Stable Diffusion tools support them directly, and Midjourney has
--no. Use them for specific unwanted elements (for example, "blurry, extra fingers"), not long lists of generic terms, which rarely help much. - Seed. If your tool lets you fix the seed, change only one setting at a time while keeping the seed constant. That shows what each change actually does.
Step 4: Targeted fixes for common failures
Hands, faces, and distorted objects
Newer models handle these better than older ones, but errors still happen, especially in crowded scenes or small faces. Make the subject larger in the frame, simplify the pose, or hide the problem area (hands in pockets, holding an object). If the rest of the image is good, don't regenerate: use inpainting or a region-edit feature (such as Midjourney's editing tools, Photoshop's Generative Fill, or the selection-based editing in some chat generators) to redo only the flawed area.
Garbled text
Text rendering has improved in some current models, but long phrases, small type, and unusual fonts remain unreliable. Put the exact wording in quotation marks, keep it to a few words, and describe where it appears. For logos, posters, or anything where spelling matters, generate the image without text and add it in Canva, Photoshop, Figma, or similar software. That is the dependable route.
Blurry or low-detail results
Check whether you are viewing a small preview. Use the tool's upscale or enhance option, or a dedicated upscaler, on the version you like. Also look for conflicting prompt words such as "soft focus," "dreamy," or "vintage film," which deliberately reduce sharpness. Upscaling adds detail but can also introduce artifacts, so compare against the original.
Off-center or badly framed subjects
State the framing ("centered, full body visible, space around the subject"). If the subject is still cropped, change the aspect ratio. Another option is to generate a wider image and crop it, or use an outpainting/extend feature where available.
Wrong style or character drift between images
Each generation starts fresh, so consistency is hard. Reuse the same wording, fix the seed if possible, or use a reference-image feature if your tool offers one. Expect similarity, not an exact match.
Step 5: Edit rather than regenerate
Once the image is about 80% right, start editing it. Rerolling from scratch tends to lose what already works. Ask for one change at a time ("keep everything the same, change the jacket to blue"), or mask the area to alter. Results are not guaranteed to preserve everything outside the edit, so save the good version before each change.
If it still looks wrong
- Test the same prompt in another tool. Models differ in strengths; a design-oriented tool may handle text, while a different one handles photorealism better.
- Check for a newer model version. Many tools let you choose a version, and newer is not always better for every style, so compare.
- Look at content rules. Some tools quietly alter or refuse prompts involving real people, brands, or sensitive subjects, which can make the output seem unrelated.
- Local Stable Diffusion setups: mismatched models, LoRAs, or VAEs commonly cause washed-out colors or distortion. Confirm each add-on is compatible with your base model, and try a clean default workflow to isolate the cause.
- Consider the task itself. Precise layouts, exact brand elements, and technical diagrams are weak spots. A manual design tool, with AI used only for background art, will often work better.
How to confirm it is fixed
Judge the fix by consistency, not one lucky result. Run the final prompt and settings four or more times. Then zoom to 100% and inspect hands, edges, text, and background details. Finally, view the image at the size you will actually use it, whether that is a social post, a print, or a slide.
Next step
Simplify the prompt, correct the aspect ratio, and fix flawed areas with local edits before reaching for advanced settings. If a specific setting is unclear, the official documentation for your tool and model version is the best source, since parameters and defaults change between releases.