Generating many images is not just a larger version of generating one image. The main challenge shifts from prompt experimentation to planning, naming, consistency, and review.
1. Build a production-ready prompt list
Create one row per intended image. Give each row a stable ID that will still make sense after download, such as product-front, product-detail, or scene-03-wide. Write each prompt so it can stand alone.
Repeat any requirement that matters across the set: subject description, palette, lighting, lens language, background treatment, and exclusions. Avoid references such as “same as above,” because each row is processed independently.
2. Paste the list or import CSV
Use pasted text for a quick set. Use CSV when the batch will be reviewed by a team, regenerated later, or assembled into another production workflow. CSV gives you an editable source of truth for IDs, prompts, and copy counts.
For messy notes, Smart Format can split the source into rows before you review them. The prompt-formatting guide explains how to avoid shifted or incomplete items.
3. Choose settings deliberately
Pick the image model, route, and aspect ratio based on the final destination. A social portrait, marketplace thumbnail, and cinematic storyboard frame should not inherit the same shape by accident.
If you are comparing models, use the same small set of representative prompts. Keep the route and aspect ratio recorded with the results so you know what produced each test.
4. Test the hard cases first
Do not start with the easiest prompt. Include the recurring subject, the busiest composition, a close-up, and any scene containing typography or precise product details. A batch of three to five tests usually exposes weaknesses in the shared prompt pattern.
Fix the prompt source, not just one output. When a character drifts, add the missing description to every affected row. When compositions are repetitive, introduce deliberate shot variation across the list.
5. Review the set as a set
Check individual quality first, then zoom out. Look for inconsistent lighting, palette drift, duplicate compositions, missing coverage, and filename ambiguity. Regenerate only the failed or weak rows instead of rerunning the whole batch.
GenBatch uses credits and charges only for successful generations. Batch capacity depends on the active workflow and provider, so check the product UI and pricing rather than planning around an old fixed limit.
