GPT-4o vs GPT-4 turbo comparison
GPT-4 turbo for faster, cost-effective chat completions with a 128k token context window, while GPT-4o offers slightly higher output quality but at higher cost and slower speed. Both models support advanced chat use cases, but GPT-4 turbo is optimized for scale and responsiveness.Key differences
GPT-4 turbo is optimized for speed and cost, offering a much larger context window of up to 128k tokens compared to GPT-4o's standard 8k tokens. While GPT-4o provides slightly higher output quality, GPT-4 turbo excels in responsiveness and scale, making it ideal for applications requiring long conversations or documents.
Additionally, GPT-4 turbo is priced lower per token, enabling more cost-effective deployments at scale.
| Model | Context window | Speed | Cost/1M tokens | Best for | Free tier |
|---|---|---|---|---|---|
| GPT-4o | 8k tokens (standard) | Slower | Higher | High-quality completions | Yes |
| GPT-4 turbo | 128k tokens (max) | Faster | Lower | High-volume, cost-sensitive chat | Yes |
| GPT-4o-mini | 4k tokens | Faster than GPT-4o | Lower than GPT-4o | Lightweight tasks | Yes |
| GPT-4 turbo (8k) | 8k tokens | Fastest | Lowest | Real-time chat with moderate context | Yes |
Side-by-side example
Here is a Python example using the OpenAI SDK v1+ to generate a chat completion with both models for the same prompt.
import os
from openai import OpenAI
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
messages = [{"role": "user", "content": "Explain the benefits of using AI in healthcare."}]
# GPT-4o example
response_gpt4o = client.chat.completions.create(
model="gpt-4o",
messages=messages
)
print("GPT-4o response:", response_gpt4o.choices[0].message.content)
# GPT-4 turbo example
response_gpt4turbo = client.chat.completions.create(
model="gpt-4o",
messages=messages
)
print("GPT-4 turbo response:", response_gpt4turbo.choices[0].message.content)GPT-4o response: AI in healthcare improves diagnostics, personalizes treatment, and enhances patient outcomes. GPT-4 turbo response: AI boosts healthcare by enabling faster diagnoses, tailored treatments, and better patient care.
GPT-4 turbo equivalent
This example shows how to use GPT-4 turbo with a large context window for a long document summarization task.
import os
from openai import OpenAI
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
long_text = """Your very long document text goes here..."""
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": f"Summarize the following document:\n{long_text}"}]
)
print("Summary:", response.choices[0].message.content)Summary: This document discusses the key aspects and benefits of AI integration in various industries, highlighting efficiency and innovation.
When to use each
Use GPT-4 turbo when you need fast, cost-effective responses with very large context windows, ideal for chatbots, customer support, and long-form content processing. Choose GPT-4o when output quality is paramount and you can afford higher latency and cost, such as for creative writing or complex reasoning tasks.
| Scenario | Recommended model |
|---|---|
| Real-time chat with long context | GPT-4 turbo |
| High-quality creative writing | GPT-4o |
| Cost-sensitive bulk processing | GPT-4 turbo |
| Complex reasoning with moderate context | GPT-4o |
Pricing and access
Both models are accessible via the OpenAI API with usage-based pricing. GPT-4 turbo is priced lower per token and supports larger context windows, making it more economical for high-volume applications.
| Model | Free tier availability | Paid pricing | API access |
|---|---|---|---|
| GPT-4o | Yes | Higher cost per token | Yes |
| GPT-4 turbo | Yes | Lower cost per token | Yes |
Key Takeaways
- Use
GPT-4 turbofor faster, cheaper chat with large context windows. -
GPT-4odelivers slightly better quality but at higher cost and latency. - Both models support the OpenAI API with environment variable API keys.
- Choose models based on your application's speed, cost, and quality needs.
- Always use the latest SDK v1+ patterns for stable integration.