Best Temperature Settings for OpenAI (2025 Guide)

Temperature controls randomness. Lower = more predictable; higher = more creative.

Supports OpenAI & Groq today • No prompt content stored

Best Temperature by Use Case

Task	Recommended	Notes
Coding, extraction, evaluation	0.0–0.3	Deterministic, testable outputs
General drafting, product copy	0.4–0.7	Balance variety with consistency
Brainstorming, story, naming	0.8–1.2	More diversity; review quality

How Temperature Changes the Style

Prompt: "Explain quantum computing in simple terms"

Temp 0.2 → “Quantum computing uses qubits, which can be 0 and 1 at once…”

Temp 0.7 → “Imagine a coin that can be both heads and tails at once…”

Temp 1.2 → “It’s like asking Schrödinger’s cat to juggle probabilities…”

Temperature vs. Top-p (Nucleus)

Temperature scales randomness across all tokens.
Top-p trims to the smallest set of tokens whose probabilities sum to p (e.g., 0.9).
Tip: adjust one at a time; start with temperature.

Set Temperature via API (copy-paste)

from openai import OpenAI
client = OpenAI()
resp = client.chat.completions.create(
  model="gpt-4o-mini",
  temperature=0.3,  # lower = more deterministic
  messages=[{"role":"user","content":"Summarize this in 3 bullets..."}]
)
print(resp.choices[0].message.content)

const r = await fetch("https://api.openai.com/v1/chat/completions",{
  method:"POST",
  headers:{
    "Authorization":`Bearer ${process.env.OPENAI_API_KEY}`,
    "Content-Type":"application/json"
  },
  body: JSON.stringify({
    model:"gpt-4o-mini",
    temperature:0.7,  // balanced drafting
    messages:[{role:"user",content:"Give 10 brand names for a coffee app"}]
  })
});
const data = await r.json();

Quick Check: Cost Impact

Estimate cost per 100 calls (using your token price). Lower temperature often reduces retries and over-long outputs.

Want real charts? Open the demo →

Privacy: We never store prompt or output content—telemetry only (token counts, timings, success). Supported today: OpenAI, Groq.

PyPI post → why the dashboard matters · See pricing

FAQs

What temperature should I use for coding?

Use a low range (0.0–0.3) for deterministic, testable answers.

What about creative work?

Try 0.8–1.2 for more variety—review outputs for quality.

Temperature vs Top-p?

Temperature controls randomness; top-p limits the token pool (nucleus). Adjust one at a time.

Can I set temperature in OpenAI ?

Not directly; set via API or tools that expose the control.