GPT-4o Model Profile: Specifications, Pricing, API Access, and Application Scenarios

What is GPT-4o?

GPT-4o is a multimodal large language model released by OpenAI in May 2024. It supports text, image, and audio inputs. The context window is 128K tokens, and API input pricing is $5 per million tokens (as of June 2026).

In GPT-4o, the “o” stands for Omni, meaning “all modalities.” Compared with earlier GPT-4 series models, GPT-4o integrates text understanding, image understanding, and voice interaction capabilities into a unified model architecture, enabling developers to build multimodal applications through a single API.

GPT-4o was officially released during OpenAI 2024 Spring Update, and is currently widely used in scenarios such as AI assistants, enterprise knowledge bases, customer service robots, code development tools, and Agent workflows.

What core specifications does GPT-4o have?

GPT-4o Specification Table (as of June 2026)

| Parameter | Value | | :--- | :--- | | Model Name | GPT-4o | | Provider | OpenAI | | Release Date | 2024-05-13 | | Context Window | 128K Tokens | | Maximum Output Length | 16K Tokens | | Input Types | Text, Image, Audio | | Output Types | Text, Audio | | Function Calling | Supported | | Structured Output | Supported | | JSON Mode | Supported | | API Input Price | 5 USD / million Tokens | | API Output Price | 15 USD / million Tokens | | Knowledge Cutoff | As per OpenAI official documentation |

What practical capabilities does GPT-4o have?

GPT-4o supports the following common large-model capabilities in production environments: | Capability | Description | | :--- | :--- | | Text Generation | Supports article writing, summarization generation, translation, multi-turn conversation, and knowledge Q&A | | Image Understanding | Supports analyzing images, charts, screenshots, documents, and other visual content | | Audio Processing | Supports voice input and voice output | | Code Development | Supports code generation, debugging, explanation, and optimization | | Agent Tool Calls | Supports Function Calling and structured output | | Multilingual Capability | Supports input and output in multiple mainstream languages |

These capabilities enable GPT-4o to handle text, visual, and speech tasks at the same time, reducing the complexity for developers when switching between different models.

What are the limitations of GPT-4o?

Like other large language models, GPT-4o still has certain limitations:

| Limitation | Description | | :--- | :--- | | Hallucination Risk | May generate inaccurate or unverified information | | Long-Context Decay | In scenarios involving extremely long documents, information may be omitted | | Non-Real-Time Knowledge | Cannot automatically retrieve the latest internet information | | Result Variability | The same question may produce different answers | | Language Differences | Performance may vary across different languages |

For high-risk scenarios such as finance, healthcare, and law, it is typically necessary to combine manual review or verification using an external knowledge base to validate the model’s output results.

What scenarios is GPT-4o suitable for?

GPT-4o is suitable for applications that need unified handling of text, images, and audio.

| Scenario | Fit Level | Typical Use | | :--- | :---: | :--- | | Software Development | High | AI programming assistant, code generation, code review | | Content Creation | High | Blogs, marketing copy, product descriptions | | Enterprise Knowledge Base | High | Internal Q&A systems, knowledge retrieval | | Intelligent Customer Service | High | Customer service robots and auto-replies | | Image Analysis | High | OCR, chart analysis, visual Q&A | | Voice Assistant | High | Real-time voice interaction applications | | Agent Systems | High | Tool calls and automated workflows | | Academic Assistance | Medium | Literature summarization and research support |

For teams hoping to build unified multimodal workflows, GPT-4o is one of the more common model choices.

How does GPT-4o differ from Claude 3.5 Sonnet and Gemini 1.5 Pro?

Core capabilities comparison (as of June 2026)

| Comparison Item | GPT-4o | Claude 3.5 Sonnet | Gemini 1.5 Pro | | :--- | :--- | :--- | :--- | | Provider | OpenAI | Anthropic | Google | | Context Window | 128K | 200K | Up to over 1 million | | Image Input | Supported | Supported | Supported | | Audio Input | Supported | Limited support | Supported | | Function Calling | Supported | Supported | Supported | | Real-Time Speech Capability | Supported | Not a core capability | Supported | | Google Ecosystem Integration | Limited | None | Deep integration |

GPT-4o supports unified processing of text, images, and audio in a single API request, so it is more suitable for multimodal collaborative processing scenarios.

Claude 3.5 Sonnet is typically used for reading long documents, knowledge analysis, and enterprise writing tasks.

Gemini 1.5 Pro is better suited for applications that require an ultra-long context window and Google ecosystem integration.

Different models are suitable for different scenarios, and there is no single universally “best” model.

How to call GPT-4o through Gate.AI?

Gate.AI provides an OpenAI-compatible API interface. Developers can access GPT-4o through a unified platform, and switch models, manage costs, and implement organization-level governance according to business needs.

Python example

Python from openai import OpenAI

client = OpenAI( api_key="YOUR_API_KEY", base_url="" )

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

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

cURL example

Bash curl /chat/completions
-H "Authorization: Bearer YOUR_API_KEY"
-H "Content-Type: application/json"
-d '{ "model":"gpt-4o", "messages":[ {"role":"user","content":"Hello"} ] }'

With Gate.AI, developers can also centrally manage API keys, model routing, cost monitoring, and organization-level permission controls, thereby reducing the complexity of deploying and governing multiple models.

FAQ

Does GPT-4o support image input?

Yes. GPT-4o can directly accept image input and analyze the text, charts, screenshots, and other visual content in the images.

What is the difference between GPT-4o and Claude 3.5 Sonnet?

GPT-4o places more emphasis on unified multimodal processing capabilities, while Claude 3.5 Sonnet is more commonly used for long-document reading and enterprise writing scenarios.

What is the price of the GPT-4o API?

As of June 2026, the GPT-4o API input price is $5 per million Tokens, and the output price is $15 per million Tokens.

Is GPT-4o suitable for code development?

Yes. GPT-4o supports tasks such as code generation, debugging, code explanation, and writing development documentation.

Is GPT-4o suitable for building an Agent system?

Yes. GPT-4o supports Function Calling, Structured Outputs, and tool-calling capabilities, so it can serve as the core reasoning model in Agent workflows.

Does GPT-4o support real-time internet access?

GPT-4o itself does not directly provide real-time internet access capability. If you need to obtain the latest information, you usually need to combine it with search tools, an RAG system, or external data sources.