Image Generation / Midjourney

Determine –c value based on desired output diversity — calibrates variation scientifically, not randomly.
Difficulty: Intermediate
Model: GPT-4 / Claude / Gemini
Use Case: Variation Control, Exploration vs. Consistency
Updated: May 2026
Why This Prompt Exists
–chaos (–c) controls how much variation you get between generations. Most users leave it at 0 (identical outputs) or crank it to 100 (unusable randomness) — missing the productive middle range.

You get:

  • chaos = 0: every generation looks the same (no exploration)
  • chaos = 100: outputs are unrecognizably different (no consistency)
  • no understanding of what different chaos values actually produce
  • wasted generations because chaos is set wrong for the task
  • inability to explore variations while keeping brand identity

But chaos values have predictable effects:

  • 0-10: Very similar outputs, minor variations in details
  • 11-30: Noticeable variations in composition and framing
  • 31-60: Significant variations, different interpretations of the prompt
  • 61-80: High variation, may change subject interpretation
  • 81-100: Extreme variation, unpredictable results

Without calibration, chaos is a guessing game.

This prompt recommends chaos values by intended variation level.

The Prompt
Assume the role of a Midjourney variation scientist who calibrates chaos parameters.

Your task is to recommend --c values based on desired output diversity.

Generate:

1. VARIATION GOAL CLASSIFICATION
   - Desired consistency: [IDENTICAL / SIMILAR / MODERATE VARIATION / HIGH VARIATION / EXPLORATION]
   - Use case type: [BRAND ASSET / CONCEPT EXPLORATION / SERIES / ONE-OFF]

2. CHAOS VALUE RECOMMENDATION TABLE

| Variation Goal | Recommended --c | Expected Output | Best For |
|----------------|-----------------|-----------------|----------|
| Identical | 0 | Same image, same seed | Reproducible assets |
| Very similar | 1-10 | Minor detail changes | Logo variants, small adjustments |
| Noticeable variation | 11-30 | Composition changes, different framing | Multiple options for same brief |
| Significant variation | 31-60 | Different interpretations | Concept exploration |
| High variation | 61-80 | May change subject interpretation | Brainstorming, early ideation |
| Extreme exploration | 81-100 | Unpredictable, experimental | Creative inspiration only |

3. USE CASE MAPPING

| Use Case | Recommended --c | Rationale |
|----------|-----------------|-----------|
| Brand logo exploration | 30-50 | Need variety but maintain recognizability |
| Character concept art | 40-70 | Explore different looks for same character |
| Product photography | 0-10 | Consistent product representation |
| Social media content | 10-30 | Fresh looks, same style |
| Print ad series | 5-20 | Consistent but not identical |
| Mood board creation | 50-80 | High variation for inspiration |

4. CHAOS COMBINATION WITH OTHER PARAMETERS
   - --c + --seed: fixed seed + chaos = variations on same theme
   - --c + high --stylize: unpredictable (use lower --c)
   - --c + --no: chaos may override negative prompts at high values

5. CHAOS CALIBRATION TEST PROTOCOL
   - Step 1: Run 4 generations at --c 0 (baseline)
   - Step 2: Run 4 generations at --c 25 (moderate variation)
   - Step 3: Run 4 generations at --c 50 (high variation)
   - Step 4: Select best value based on output

6. COMMON MISTAKES TO AVOID
   - Using --c 0 for exploration (wasted generations, no variety)
   - Using --c 100 for brand assets (inconsistent, unusable)
   - Expecting chaos to create variation within one generation (it affects multiple runs)
   - Combining high chaos with high stylize (too unpredictable)

INPUTS:

Desired consistency level:
[IDENTICAL / SIMILAR / MODERATE / HIGH / EXTREME]

Use case:
[E.G., "Brand logo exploration", "Product photos", "Concept art"]

Number of variations needed:
[E.G., "10-20 options to choose from"]

Subject type:
[E.G., "Abstract", "Realistic product", "Character", "Landscape"]

RULES:
- --c controls variation across multiple generations, not within one image
- Lower chaos (1-10) for brand consistency where identity matters
- Medium chaos (30-50) for concept exploration where variety is valuable
- High chaos (70-100) for brainstorming only — not final assets
- Test chaos at 25, 50, and 75 to understand your specific prompt's sensitivity
- Some prompts are more chaos-sensitive than others (abstract prompts vary more)
How To Use It
  • –c controls variation across multiple generations, not within a single image.
  • Lower chaos (1-10) for brand consistency where identity matters.
  • Medium chaos (30-50) for concept exploration where variety is valuable.
  • High chaos (70-100) for brainstorming only — not for final assets.
  • Test chaos at 25, 50, and 75 to understand your specific prompt’s sensitivity.
  • Some prompts are more chaos-sensitive than others (abstract prompts vary more).
Example Input

Desired consistency level:
“MODERATE — want different options but same character”

Use case:
“Character concept art for a game protagonist”

Number of variations needed:
“20-30 options to choose from”

Subject type:
“Character — fantasy warrior”

Why It Works
Most users treat chaos as a binary choice — off or maximum — missing the graduated scale that makes it useful.

This framework improves outcomes by forcing:

  • variation goal classification (identical to extreme exploration)
  • chaos value mapping (specific ranges for specific outcomes)
  • use case alignment (brand assets vs. concept exploration)
  • parameter interaction awareness (chaos + stylize, chaos + no)
  • calibration test protocol (finding the right value for your prompt)

Failure modes this prevents:

  • Chaos = 0 for exploration (all outputs identical, no variety)
  • Chaos = 100 for brand assets (outputs unrecognizable, unusable)
  • Expecting chaos to vary within one generation (it affects multiple runs)
  • Combining high chaos with high stylize (too unpredictable)

This improves on: Random chaos guessing. Calibrated variation produces useful diversity without unusable outputs.

Related to: MJ-01 (Parameters) for chaos syntax; MJ-06 (Remix) for variation patterns.

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See also  Remix Pattern Detector