What Is GPT-4o?
GPT-4o ("o" for omni) is OpenAI's flagship multimodal model that processes text, images, and audio natively in a single unified architecture. Unlike earlier models that bolted vision onto a language backbone, GPT-4o was trained end-to-end across all modalities — making it faster and more coherent when reasoning across mixed inputs.
As of 2026, it remains the go-to model for applications that need strong general reasoning combined with vision capabilities.
Pricing and Context Window
GPT-4o is priced at $2.50 per million input tokens and $10.00 per million output tokens via the OpenAI API. It supports a 128k token context window, meaning you can pass in roughly 300 pages of text in a single request.
For cost-sensitive workloads, GPT-4o mini cuts the price to $0.15/1M input tokens with a modest quality tradeoff — covered in a separate post.
Calling the API With Python
Getting started with the OpenAI Python library is straightforward:
from openai import OpenAI
client = OpenAI() # reads OPENAI_API_KEY from env
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Explain transformer attention in one paragraph."}
],
max_tokens=512,
temperature=0.7,
)
print(response.choices[0].message.content)
For streaming responses (lower time-to-first-token in production):
with client.chat.completions.stream(
model="gpt-4o",
messages=[{"role": "user", "content": "Write a haiku about embeddings."}],
) as stream:
for text in stream.text_stream:
print(text, end="", flush=True)
Vision Capabilities
Pass images by URL or as base64. This is useful for document parsing, UI analysis, and chart extraction:
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What does this chart show?"},
{
"type": "image_url",
"image_url": {"url": "https://example.com/chart.png"},
},
],
}
],
)
The model can read handwritten text, interpret diagrams, describe photographs, and even reason about spatial relationships in images — all within the same request that might also include long text context.
GPT-4o vs GPT-4o Mini
Use GPT-4o when you need:
- Complex multi-step reasoning over long documents
- High-stakes code generation or debugging
- Vision tasks requiring nuanced understanding
- Instruction-following fidelity in agentic pipelines
Use GPT-4o mini when you need:
- High-volume classification, extraction, or summarization
- Latency-sensitive user-facing features
- Cost below $0.20/1M input tokens
Summary
GPT-4o is the workhorse of OpenAI's lineup — strong across text, code, and vision with a 128k context that covers most real-world documents. Start with it for new projects, measure quality and cost, then route simpler tasks to GPT-4o mini once you have baseline metrics. Full model documentation lives at platform.openai.com.
