Nano Banana 2 Character Consistency: How to Keep the Same Character Across Images

Character consistency in Nano Banana 2 comes down to two things: a reference image that anchors the face and outfit, and a prompt that separates identity details from scene details. If you supply only a text description, expect the character to drift between generations. If you supply a reference image plus a short, structured identity block, you can reuse the same character across poses, scenes, and outfits with far fewer retries. This workflow applies to any image-editing session in the HeyMarmot workspace, where Nano Banana 2 runs alongside other models.

What character consistency means here

Consistency means the same person reads as the same person across multiple outputs — same facial structure, hair, skin tone, and signature clothing — even when the pose, background, or lighting changes.

Drift happens because image models regenerate the character from scratch each time. Nothing in a plain text prompt pins down "this exact face." Words like "a young woman with brown hair" describe a category, not a person, so every generation samples a different individual from that category.

Two levers reduce drift:

• A reference image carries the visual identity the prompt can't describe precisely.
• A locked identity block in the prompt keeps the details the reference can't fully control (exact outfit, color palette, distinguishing marks).

Use both. A reference image alone can still shift clothing and color; a prompt alone can't hold a face.

Build a reusable character reference

Do this once, then reuse it for every subsequent image.

Step 1 — Generate a clean base portrait. Create a single, front-facing image of your character with neutral lighting and a plain background. Avoid dramatic angles, heavy shadows, or busy scenes — those make the reference harder for the model to read.

Step 2 — Write an identity block. This is a short, fixed paragraph you paste into every prompt. Cover:

• Face: age range, face shape, distinguishing features
• Hair: color, length, texture, style
• Skin tone
• Outfit: specific garment, color, and material
• Palette: two or three dominant colors
• One or two unique marks (a scar, a specific accessory, a logo)

Keep it under about 60 words. Longer blocks dilute the signal.

Step 3 — Test the block. Generate three images with the same identity block and the same reference image, changing only the scene. If the character holds across all three, the block is working. If not, tighten the vague parts — usually hair and outfit.

Step-by-step: consistent character across new scenes

1. Upload your reference image as the visual anchor for the generation.
2. Paste the identity block at the start of the prompt, unchanged from previous runs.
3. Add the scene instruction after the identity block — new pose, background, action, or lighting.
4. Generate one image first. Check the face and outfit before committing to a batch.
5. Iterate on the scene only. If the character is right but the scene is wrong, edit the scene text and leave the identity block untouched.
6. Reuse the winning output as the new reference if you're moving to a very different angle or outfit, so the model has a fresh anchor.

The key discipline: never change the identity block and the scene at the same time. If something breaks, you won't know which change caused it.

Prompt patterns that lock identity while allowing scene changes

Structure your prompt in two clearly separated parts.

Identity block (fixed):

A woman in her late 20s, oval face, sharp jawline, dark brown wavy shoulder-length hair, warm medium skin tone, wearing a fitted charcoal turtleneck, small silver hoop earrings, a thin scar above the left eyebrow. Palette: charcoal, silver, warm beige.

Scene block (variable):

Standing in a rain-soaked neon alley at night, looking over her shoulder, cinematic lighting.

Swap only the scene block for each new image. This keeps the model's attention on the same identity while the environment changes freely.

For outfit changes, add an explicit override line rather than rewriting the identity block:

Keep the same face, hair, and skin tone. Change outfit to a cream linen shirt.

This tells the model which parts are allowed to move.

Common failure causes and fixes

The most common mistake is stacking edits. Each round of editing nudges the character slightly, and after four or five rounds the face is gone. Re-anchor from the original reference whenever you notice drift starting.

Planning credits around iteration

Consistency work is iterative, so budget for retries rather than expecting a first-try match. The HeyMarmot workspace provides free starter credits on sign-up, and continued use is paid — check the pricing page for current rates before a long session.

Practical planning:

• Front-load the work. Spend your first few generations nailing the base portrait and identity block. Every later image gets cheaper because you retry less.
• Generate one, then batch. Test a single image before running a set. A failed batch wastes far more credits than a failed single.
• Keep a reference library. Save your best base portrait and two or three approved scene images. Reusing them as anchors cuts retries on future projects.

Quick checklist

• One clean reference image, front-facing, neutral background
• Identity block under 60 words, pasted unchanged every time
• Scene instructions in a separate block, changed one variable at a time
• Re-anchor from the original reference when drift appears
• Test single images before batching to control credit spend