AI Character Reference Generation

Create 17+ consistent character poses from detailed prompts — no reference images needed.

⚠️ Staleness Watch (Last validated: Feb 2026 — Flux 1.1 Pro): Image generation models on Replicate release new versions and deprecate old ones. Before generating, verify the model identifier at replicate.com/black-forest-labs. Upgrade path: black-forest-labs/flux-1.1-pro-ultra provides higher resolution (up to 4MP) with the same API surface. Input parameter schema may change between model versions.

Model Selection Guide

Recommended Models by Use Case

Use Case	Model	Cost	Notes
Face Consistency (Default)	`google/nano-banana-pro`	$0.025/image	Best for maintaining face identity — uses reference image + prompt. Maintains Alex identity across 90+ avatar images.
Detailed Scenes	`black-forest-labs/flux-1.1-pro`	$0.04/image	High-quality scenes without face reference. Good for backgrounds and environments.
Agent Banners	`ideogram-ai/ideogram-v2`	$0.08/image	Best for stylized text + character combinations. Prominent branding.
High Resolution	`black-forest-labs/flux-1.1-pro-ultra`	$0.06/image	Up to 4MP output. Use when print-quality needed.

Face Consistency Pattern (Nano-Banana Pro)

The Key Insight: For consistent character faces across multiple poses/scenarios, use a reference face image with nano-banana-pro:

const response = await replicate.run("google/nano-banana-pro", {
  input: {
    prompt: `${CHARACTER_DESC}, ${scenario.attire}, ${scenario.pose}, ${STYLE}`,
    image: await toDataURI("path/to/reference-face.png"),  // Key: face reference
    aspect_ratio: "1:1",  // Square for avatars
    output_format: "png"
  }
});

Cost Analysis:

90 avatar images × $0.025 = $2.25 total (nano-banana)
vs 90 × $0.04 = $3.60 (Flux 1.1 Pro)
Savings: 37.5% while maintaining face consistency

Summary

Complete workflow for generating consistent visual character references across multiple scenarios using Flux 1.1 Pro API. Validated through 51 successful image generations across 3 character types.

Critical Insight: Character Consistency Without Reference Images

Common Misconception: Use image_prompt parameter with reference photo for consistency

Reality:

image_prompt = Flux Redux composition guidance (NOT character consistency)
Character consistency comes from detailed text descriptions
Pose variety comes from explicit body position descriptions

Prompt Engineering Pattern

const PROMPT_TEMPLATE = `
${CHARACTER_DESC},          // Detailed physical description
${scenario.attire},         // Scene-appropriate clothing
${scenario.scenario},       // Narrative context
${scenario.pose},          // EXPLICIT body position/gesture
${scenario.environment},   // Setting details
${scenario.lighting},      // Light sources and mood
${scenario.mood},          // Emotional tone
${STYLE_BASE}              // Aesthetic/rendering style
`;

Critical Success Factors

Detailed CHARACTER_DESC (creates consistency):

const CHARACTER_DESC = "Alex Finch, 21, sharp intelligent features, " +
  "short dark brown hair with copper highlights, athletic build, " +
  "confident but approachable demeanor, piercing analytical eyes";

Explicit Pose Descriptions (creates variety):
- ❌ Vague: "standing in office"
- ✅ Specific: "leaning forward with both hands on desk, analyzing data intently"
- ✅ Specific: "standing with one hand gesturing toward display, explaining concept"

Style Consistency:

// Detective Noir
const STYLE_BASE = "Professional illustration, high contrast noir lighting, " +
  "dramatic shadows, cinematic composition, sharp detail, moody atmosphere";

// Fantasy Wonderland
const STYLE_BASE = "Soft fantasy illustration, pastel color harmony, " +
  "ethereal glow, magical atmosphere, dreamy composition";

Character-Agnostic Template Structure

// Configuration Block (customize per character)
const CHARACTER = {
  name: "Character Name",
  description: "detailed physical appearance",
  age: number
};

const STYLE = "aesthetic appropriate to narrative";

const SCENARIOS = [
  {
    id: "001",
    title: "Scene Title",
    scenario: "narrative context",
    attire: "specific clothing details",
    pose: "EXPLICIT body position, hands, gaze",
    environment: "setting details",
    lighting: "light sources and mood",
    mood: "emotional tone"
  }
  // ... 16 more scenarios
];

// Generation Engine (reusable)
async function generateScene(scenario) {
  const prompt = buildPrompt(CHARACTER, scenario, STYLE);
  return await replicate.run("black-forest-labs/flux-1.1-pro", {
    input: {
      prompt,
      aspect_ratio: "3:4",
      output_format: "png",
      output_quality: 100,
      safety_tolerance: 2
    }
  });
}

Validated Results

Successful Generations (Feb 2026):

Alex: 17/17 professional noir scenes
Iris: 17/17 wonderland magic scenes
Maya: 17/17 teen life scenes

Quality Metrics:

100% generation success rate (with retry handling)
17 unique poses per character
Visual consistency maintained across all images
Style consistency within each aesthetic type

Troubleshooting

Safety Filter False Positives

Issue: Child character poses sometimes trigger safety filters

Example: "sitting on ground, knees drawn up" (blocked)

Solution: Adjust to neutral poses: "sitting cross-legged leaning forward"

Pattern: Avoid poses that could be misinterpreted for child characters

Rate Limiting

Issue: 429 Too Many Requests from Replicate API

Solution: Exponential backoff retry pattern

async function retryWithBackoff(fn, maxRetries = 3) {
  for (let i = 0; i < maxRetries; i++) {
    try {
      return await fn();
    } catch (error) {
      if (error.response?.status === 429 && i < maxRetries - 1) {
        const delay = 2000 * Math.pow(2, i);
        await new Promise(r => setTimeout(r, delay));
        continue;
      }
      throw error;
    }
  }
}

Pose Repetition

Symptom: All images show similar body positions

Diagnosis: Pose descriptions too vague

Fix: Be cinematically specific

✅ "leaning against doorframe, arms crossed, skeptical expression"
✅ "crouched examining ground, one hand touching surface"
✅ "mid-stride walking forward, confident purposeful movement"

Cost and Performance

Default: Nano-Banana Pro (Face Consistency)

Model: google/nano-banana-pro (recommended)
Cost: $0.025 per image
Generation Time: ~15-30 seconds per image
Best For: Character avatars, portraits, face consistency
Requires: Reference face image

Alternative: Flux 1.1 Pro (Scene Flexibility)

Model: black-forest-labs/flux-1.1-pro
Cost: $0.04 per image
Generation Time: ~30-60 seconds per image
Best For: Full scenes, no reference image needed
Aspect Ratio: 3:4 portrait recommended
Output Format: PNG at quality 100 for archival

Economic Comparison:

Character Set	Nano-Banana	Flux 1.1 Pro
17 scenarios	$0.43	$0.68
90 avatars	$2.25	$3.60
Full set (100+)	~$2.50	~$4.00

Cross-Project Applicability

Use Cases:

Book character reference sheets
Visual novel character consistency
Game concept art
Marketing material uniformity
Story illustration preparation

Character Types Validated:

Young adult detective (noir aesthetic)
Teen fantasy character (ethereal aesthetic)
Contemporary teenager (realistic aesthetic)

Implementation

Dependencies:

Replicate API account and token
Node.js with ES modules support

File Organization:

characters/
  {character-slug}/
    images/
      {collection-name}/
        001-{scenario-title}.png
        002-{scenario-title}.png
        generation-report.json

Package.json script:

"scripts": {
  "generate:character": "node scripts/generate-character-reference.js"
}

Confidence Level

High — Empirically validated through:

51 successful image generations
3 different character types
3 different aesthetic styles
100% success rate (with retry handling)