How to Create Consistent AI Characters Across Multiple Images

One of the biggest challenges in AI image generation is keeping a character looking the same across multiple images. You create a perfect character in one shot — right face, right outfit, right vibe — and then in the next image, they look like a completely different person. This guide walks you through everything you need to know about creating and maintaining consistent AI characters, from the technology behind it to a hands-on tutorial using Apefx.

Why Character Consistency Matters

Character consistency isn’t just a nice-to-have — it’s essential for any project that involves visual storytelling. Consider the use cases:

• Comic books and graphic novels: Your protagonist needs to look the same across dozens or hundreds of panels
• Marketing campaigns: A brand mascot must be immediately recognizable across all touchpoints
• Film pre-visualization: Storyboards only work if the director can track which character is which
• Children’s books: Young readers rely on visual consistency to follow a story
• Social media content: Recurring characters build audience familiarity and engagement
• Game concept art: Character design requires maintaining identity across poses, outfits, and environments

Without consistency, every image exists in isolation. With it, you can tell stories, build brands, and create cohesive visual worlds.

The Consistency Problem in AI Image Generation

Standard AI image generation works by interpreting a text prompt and generating an image from scratch. Each generation is independent — the model has no memory of what it produced before. Even if you use the exact same prompt, you’ll get a different face, different proportions, and different details every time.

This happens because of how diffusion models work. They start with random noise and gradually denoise it into an image guided by your prompt. That initial noise is different each time (unless you fix the seed), so the output varies. Fixing the seed helps with reproducibility but not with generating the same character in different poses, outfits, or environments — because the prompt changes, so does the output.

Early workarounds included:

• Detailed text descriptions: Writing extremely specific descriptions of facial features, hair, eye color, etc. This helps but never achieves true consistency
• Seed locking: Using the same random seed across generations. Somewhat useful but breaks when you change the prompt significantly
• LoRA fine-tuning: Training a small adapter model on reference images of your character. Effective but requires technical knowledge, compute resources, and hours of training per character

None of these solutions is practical for most creators. What changed everything was IP-Adapter technology and character profile systems.

How IP-Adapter Technology Works

IP-Adapter (Image Prompt Adapter) is a technology that allows you to pass a reference image to an AI model alongside your text prompt. The model uses the reference image to extract visual features — face structure, hair style, clothing details, color palette — and applies them to the new generation.

Think of it as showing the AI a photo and saying “generate someone who looks like this, but in a different scene.” The text prompt controls the new scene, pose, and context, while the reference image controls the character’s identity.

Key concepts:

• Identity extraction: The adapter extracts high-level identity features (face shape, eye color, hair) from reference images
• Style separation: Good implementations separate identity from style — your character keeps their face even when the art style changes
• Strength control: You can dial the reference influence up or down. Higher values mean closer identity matching; lower values allow more creative variation
• Multi-reference: Some systems accept multiple reference images, building a more robust understanding of the character from different angles

Models like Nano Banana Pro use this technology natively — character consistency is built into the model architecture, not bolted on as an afterthought.

Character Profiles on Apefx

Apefx’s character profile system takes IP-Adapter concepts and wraps them in a user-friendly interface. Instead of manually attaching reference images to every generation, you create a character profile once and reuse it across all your projects.

A character profile includes:

• Name: For your own organization (e.g., “Maya — protagonist”)
• Reference images: 1–5 images showing the character from different angles and in different lighting conditions
• Description: A text description of key visual traits that supplements the reference images
• Consistency strength: How strictly the model should match the reference (adjustable per generation)

The Creator plan includes 3 character profiles. The Pro plan offers unlimited profiles. When generating images, you simply select a character profile and the model automatically applies the identity features to your new generation.

Step-by-Step Tutorial: Creating a Consistent Character

Let’s walk through the complete workflow for creating and using a consistent character on Apefx.

Step 1: Generate Your Base Character

Start by generating the initial character image that defines their look. Use a detailed prompt:

Use Nano Banana Pro (15 credits) for the best character consistency support, or Flux Pro (5 credits) for a cost-effective starting point. Generate 4–6 variations and pick the one that best matches your vision.

Step 2: Generate Additional Reference Angles

One reference image is good; three are better. Using your chosen base image, generate 2–3 more reference images showing the character from different angles:

• Front-facing, well-lit (the “passport photo” reference)
• Three-quarter profile view
• Full body shot showing proportions and style

Use the image editing tools to ensure each reference maintains the character’s key features. The more diverse but consistent your references, the better the profile will perform.

Step 3: Create the Character Profile

Navigate to Characters and create a new profile:

1. Upload your 3 best reference images
2. Name the character (e.g., “Elena”)
3. Add a description: “Young woman, mid-20s, short auburn hair, green eyes, freckles, lean build”
4. Save the profile

Step 4: Generate New Scenes with Your Character

Now generate new images with your character in different contexts. Select the character profile, then write prompts focused on the scene rather than the character’s appearance:

The model will place Elena in the new scene while maintaining her facial features, hair style, and overall look. You focus on the story; the model handles the consistency.

Step 5: Use in Storyboards

For multi-shot narratives, bring your character into the storyboard editor. The MultiShot Master model (50 credits) is specifically designed for generating multi-shot sequences with character consistency — 9 coordinated shots where the same characters appear throughout the narrative.

Best Models for Character Consistency

Not all models handle character consistency equally. Here’s how Apefx’s models rank for this task:

For best results, use Nano Banana Pro for hero shots and key scenes, then Nano Banana 2 for fill-in shots where slight variation is acceptable.

Advanced Techniques

Multi-Character Scenes

When a scene includes multiple consistent characters, create separate profiles for each character. In your prompt, reference both characters and the model will attempt to maintain both identities. For complex scenes, generate each character separately and use the image editing tools to composite them.

Outfit Changes

Character consistency doesn’t mean every image must have the same outfit. The profile locks facial features and body type, not clothing. You can describe new outfits in your prompt while maintaining character identity:

Style Transfer with Consistency

You can maintain character identity while changing art styles. Generate Elena as a watercolor painting, an anime character, or a pixel art sprite — the profile preserves identity features while the prompt and model choice control the style. This is powerful for creating diverse content featuring the same character.

Aging and Variants

For stories that span time, you can create multiple profiles for the same character at different ages. Create “Elena — Age 10,” “Elena — Age 25,” and “Elena — Age 60” as separate profiles, each with appropriate reference images. The underlying facial structure will be similar enough to read as the same person.

Common Mistakes to Avoid

• Using only one reference image: A single reference gives the model limited information. Use 3–5 references from different angles for best results
• Low-quality references: Blurry, poorly lit, or heavily stylized reference images produce inconsistent results. Use clear, well-lit photos
• Over-describing the character in prompts: When using a character profile, focus your prompt on the scene. Over-describing the character can conflict with the profile and produce inconsistencies
• Ignoring lighting: Dramatic lighting changes can make the same character look different. If consistency is critical, use similar lighting across generations
• Expecting perfection: AI character consistency is very good but not pixel-perfect. Minor variations in details like exact hair strand placement are normal. The overall identity — face, build, key features — will be consistent

Character consistency transforms AI image generation from a novelty into a professional storytelling tool. With Apefx’s character profiles and models like Nano Banana Pro, you can build entire visual worlds where characters maintain their identity across hundreds of generations. Start with a strong reference set, choose the right model, and let the technology handle the rest.