Best For Intermediate · 3 min read

Best prompting techniques for GPT-4o

Quick answer

Use clear, explicit instructions with context and examples when prompting gpt-4o. Employ step-by-step reasoning and specify output format to maximize response relevance and accuracy.

RECOMMENDATION

For best results with gpt-4o, use explicit, detailed prompts that include context, examples, and clear instructions to guide the model’s reasoning and output format.

Use case	Best choice	Why	Runner-up
Code generation	`gpt-4o` with explicit step-by-step instructions	It excels at following detailed instructions and producing accurate code snippets.	`claude-3-5-sonnet-20241022`
Creative writing	`gpt-4o` with contextual setup and style examples	Provides coherent, creative outputs when given style and tone context.	`gemini-1.5-pro`
Data extraction	`gpt-4o` with clear field definitions and examples	Accurately extracts structured data when prompted with explicit schemas.	`llama-3.1-70b`
Summarization	`gpt-4o` with concise instructions and length limits	Delivers focused summaries when length and style are specified.	`mistral-large-latest`

Top picks explained

Use gpt-4o for most prompting tasks because it handles detailed instructions and context well, producing accurate and relevant outputs. For coding, explicit step-by-step prompts improve correctness. For creative tasks, adding style and tone examples guides the model’s voice effectively. When extracting data, defining fields and providing examples ensures precise results.

In practice

python

from openai import OpenAI
import os

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

prompt = (
    "You are a helpful assistant. Generate Python code that calculates the factorial of a number. "
    "Explain each step in comments. Output only the code."
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": prompt}]
)

print(response.choices[0].message.content)

output

def factorial(n):
    # Base case: factorial of 0 or 1 is 1
    if n <= 1:
        return 1
    # Recursive case: n * factorial of (n-1)
    return n * factorial(n - 1)

Pricing and limits

Option	Free	Cost	Limits	Context window
`gpt-4o`	Yes, limited tokens per month	$0.03 / 1K tokens (prompt + completion)	Max 32K tokens per request	32,768 tokens
`claude-3-5-sonnet-20241022`	Yes, limited tokens per month	$0.015 / 1K tokens	Max 100K tokens per request	100,000 tokens
`gemini-1.5-pro`	Yes, limited tokens per month	Check pricing at Google Cloud	Max 8K tokens per request	8,192 tokens

What to avoid

Avoid vague or ambiguous prompts; gpt-4o performs best with clear, explicit instructions.
Do not rely on implicit context; always provide necessary background or examples.
Avoid overly long single prompts without chunking; respect token limits to prevent truncation.
Do not expect perfect output without specifying format or constraints.

✅

Key Takeaways

Explicit, detailed prompts with examples maximize gpt-4o output quality.
Specify output format and constraints to guide the model effectively.
Chunk long inputs and provide context to avoid token limit issues.

Verified 2026-04 · gpt-4o, claude-3-5-sonnet-20241022, gemini-1.5-pro, llama-3.1-70b, mistral-large-latest

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