Skip to main content

Temperature Guide

Master the temperature parameter to control creativity and consistency in AI responses.

What is Temperature?​

Temperature controls the randomness of AI responses on a scale from 0.0 to 2.0.

0.0 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.0
    Deterministic                      Random
    Consistent                         Creative
    Focused                            Diverse

How It Works​

Low Temperature (0.0 - 0.3)​

Behavior: Predictable, consistent, focused

Characteristics:

  • ✅ Same input → Same output (mostly)
  • ✅ Picks most probable tokens
  • ✅ Factual and conservative
  • ❌ Less creative
  • ❌ Can be repetitive

Use When:

  • Factual accuracy is critical
  • Consistency matters
  • Following templates
  • Data extraction
  • Classification tasks

Examples:

Temperature: 0.1
Prompt: "What is 2+2?"
Response: "4" (always)

Temperature: 0.1
Prompt: "Classify this email as spam or not spam"
Response: Highly consistent classification

Medium Temperature (0.4 - 0.9)​

Behavior: Balanced creativity and consistency

Characteristics:

  • ✅ Good variety
  • ✅ Mostly coherent
  • ✅ Creative but controlled
  • ✅ Natural-sounding responses

Use When:

  • General conversation
  • Customer support
  • Content generation
  • Most use cases

Examples:

Temperature: 0.7 (DEFAULT - RECOMMENDED)
Prompt: "Write a welcoming email to a new customer"
Response: Friendly, natural, varied responses

High Temperature (1.0 - 2.0)​

Behavior: Creative, diverse, unpredictable

Characteristics:

  • ✅ Highly creative
  • ✅ Unexpected ideas
  • ✅ Diverse outputs
  • ❌ Less factual
  • ❌ May be incoherent
  • ❌ Unpredictable quality

Use When:

  • Creative writing
  • Brainstorming
  • Generating diverse options
  • Experimental prompts

Examples:

Temperature: 1.5
Prompt: "Write a creative product description"
Response: Highly varied, creative, sometimes unexpected

Temperature by Use Case​

Use CaseRecommended TemperatureWhy
Code Generation0.2 - 0.4Need accuracy, syntax correctness
Data Extraction0.0 - 0.2Consistency critical
Classification0.0 - 0.3Same input should give same category
Customer Support0.5 - 0.8Balance helpful & natural
Content Writing0.7 - 1.0Creative but coherent
Brainstorming1.0 - 1.5Maximum creativity
Translation0.3 - 0.5Accurate but natural
Summarization0.3 - 0.6Factual with some flexibility

Visual Examples​

Temperature: 0.0​

Prompt: "Suggest a name for a tech startup"

Run 1: "TechVentures"
Run 2: "TechVentures"
Run 3: "TechVentures"
Run 4: "TechVentures"
Run 5: "TechVentures"

Result: Identical responses

Temperature: 0.7​

Prompt: "Suggest a name for a tech startup"

Run 1: "InnovateTech Solutions"
Run 2: "NexGen Dynamics"
Run 3: "CloudSphere Technologies"
Run 4: "DataPulse Systems"
Run 5: "TechFusion Labs"

Result: Varied but reasonable

Temperature: 1.8​

Prompt: "Suggest a name for a tech startup"

Run 1: "Quantum Banana Ventures"
Run 2: "Cyber Dolphin Matrix"
Run 3: "Nebula Pickle Systems"
Run 4: "Digital Moonbeam Corp"
Run 5: "Fractal Waffle Technologies"

Result: Very creative, sometimes nonsensical

Common Mistakes​

❌ Mistake 1: Using High Temperature for Facts​

Temperature: 1.5
Prompt: "What is the capital of France?"
Response: "Paris... or maybe Lyon... I think it's Paris"

FIX: Use temperature 0.0-0.2 for factual questions

❌ Mistake 2: Using Low Temperature for Creativity​

Temperature: 0.0
Prompt: "Write a creative story about a dragon"
Response: [Same generic story every time]

FIX: Use temperature 0.8-1.2 for creative content

❌ Mistake 3: Forgetting to Test​

Problem: Assumed temperature 0.7 works for everything

FIX: Test different temperatures for your specific use case

Testing Strategy​

Step 1: Start with Defaults​

Begin at temperature 0.7 (the default for most models).

Step 2: Test Consistency​

Run the same prompt 5 times:

  • Too similar? → Increase temperature
  • Too varied? → Decrease temperature

Step 3: Evaluate Quality​

Check if responses meet your standards:

  • Too generic? → Increase temperature
  • Too random? → Decrease temperature

Step 4: Find Your Range​

Most use cases work well between 0.5 - 0.9.

Advanced Tips​

Tip 1: Combine with Top-P​

Use both temperature and top-p for fine control:

{
  temperature: 0.8,  // Allow creativity
  top_p: 0.9         // But limit to top 90% probable tokens
}

Tip 2: Different Temperatures for Different Stages​

// Planning stage: Low temperature
planningTemp = 0.3

// Execution stage: Medium temperature
executionTemp = 0.7

// Creative flourish: Higher temperature
creativeTemp = 1.0

Tip 3: Temperature Scheduling​

// Start conservative, get more creative
initialTemp = 0.5
if (needsMoreCreativity) {
  temperature = 0.8
}

Quick Reference​

Temperature Cheat Sheet​

0.0 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.0

0.0-0.2  │ ✅ Facts, Extraction, Classification
         │ ❌ Creative Writing
         
0.3-0.5  │ ✅ Code, Translation, Summarization
         │ ❌ Brainstorming
         
0.6-0.9  │ ✅ General Use, Support, Content
         │ 👍 DEFAULT RANGE
         
1.0-1.5  │ ✅ Creative Writing, Brainstorming
         │ ❌ Facts, Consistency
         
1.6-2.0  │ ✅ Experimental, Artistic
         │ ❌ Most practical uses

Testing Template​

Use this template to find your optimal temperature:

## Temperature Test

**Prompt:** [Your prompt here]
**Use Case:** [e.g., customer support]
**Quality Criteria:** [e.g., helpful, professional, accurate]

### Temperature 0.3
- Run 1: [Response]
- Run 2: [Response]
- Run 3: [Response]
- **Assessment:** Too similar/different? Quality good?

### Temperature 0.7
- Run 1: [Response]
- Run 2: [Response]
- Run 3: [Response]
- **Assessment:** Too similar/different? Quality good?

### Temperature 1.0
- Run 1: [Response]
- Run 2: [Response]
- Run 3: [Response]
- **Assessment:** Too similar/different? Quality good?

**Conclusion:** Optimal temperature = [X]

Master temperature control to get the perfect balance of creativity and consistency for your use case.