o3: Complete specifications, pricing, API integration, and application scenarios (2026)

What is o3?

o3 is a reasoning model launched by OpenAI, released on April 16, 2025, with a context window of 200k tokens, capable of advanced reasoning in text, code, and image domains. As of June 2026, API pricing is $2.00 per million input tokens and $8.00 per million output tokens. OpenAI's model page describes o3 as suitable for scenarios involving mathematics, science, programming, visual reasoning, technical writing, and multi-step instruction following.

OpenAI's o series models are designed primarily for reasoning quality over response speed. Users often compare o3 with general multimodal models like GPT-4o, low-cost alternatives like GPT-4o mini, and high-speed multimodal models like Gemini 2.0 Flash.

What are the key specifications and pricing of o3?

The table below distinguishes between OpenAI's official specifications and Gate.AI access details. OpenAI is the source for o3's official model specs and token pricing; Gate.AI documentation verifies the OpenAI-compatible API base URL and chat-completions endpoint.

| Field | Value | | -------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Provider | OpenAI (as of June 2026) | | Model Series | OpenAI o series reasoning models (as of June 2026) | | Model Type | Complex reasoning models (as of June 2026) | | Release Date | April 16, 2025 (as of June 2026) | | Context Window | 200,000 tokens (as of June 2026) | | Max Output Tokens | 100,000 tokens (as of June 2026) | | Input Pricing | OpenAI's published API price: $2.00 per million input tokens (as of June 2026) | | Cached Input Pricing | OpenAI's published API price: $0.50 per million cached input tokens (as of June 2026) | | Output Pricing | OpenAI's published API price: $8.00 per million output tokens (as of June 2026) | | Pricing Unit | Per million text tokens (as of June 2026) | | Modal Support | Supports text input/output, image input; does not support audio or video (as of June 2026) | | Supported Input Types | Text, images (as of June 2026) | | Supported Output Types | Text (as of June 2026) | | API Access | OpenAI API; Gate.AI OpenAI-compatible API, using openai/o3 as the Gate.AI model ID (as of June 2026) | | Model ID | OpenAI: o3; OpenAI snapshot: o3-2025-04-16; Gate.AI: openai/o3 (as of June 2026) | | Availability | OpenAI API; Gate.AI API via OpenAI-compatible chat completions (as of June 2026) | | Knowledge Cutoff Date | June 1, 2024 (as of June 2026) | | Request Rate Limits | Divided by OpenAI tiers; free tier not supported per OpenAI's published rate table (as of June 2026) | | Fine-tuning Support | Not supported according to OpenAI model page (as of June 2026) | | Streaming Output Support | Supported on OpenAI model page and Gate.AI chat-completions documentation (as of June 2026) | | Batch API Support | Supported via v1/batch by OpenAI (as of June 2026) | | Tool/Function Calls | Supported according to OpenAI model page (as of June 2026) | | Structured Output / JSON Mode | Supported on OpenAI model page (as of June 2026) | | Licensing / Usage Restrictions | Governed by OpenAI and Gate.AI terms; no model-specific license listed on model page (as of June 2026) |

What is the main value of o3 in production?

When tasks require deep reasoning rather than fast conversational output, o3 is especially suitable. It can be used for complex code reviews, technical design analysis, mathematical and scientific reasoning, long document interpretation, and image reasoning when input includes charts, flowcharts, or screenshots. OpenAI lists that o3 supports text and image inputs, text outputs, function calls, structured outputs, streaming, and reasoning tokens.

In production systems, o3 fits workflows where shallow answers are more costly than slow reasoning. Examples include architecture reviews, policy draft analysis, scientific problem decomposition, debugging support, and structured planning. For sensitive decisions, retrieval, verification, monitoring, and human review are still necessary.

What modalities does o3 support?

| Modality | Supported | Notes | | -------------------- | --------- | ----------------------------------------------------------------------------------------- | | Text Input | Yes | Supports prompts, instructions, code, and document content (as of June 2026) | | Text Output | Yes | Main output type (as of June 2026) | | Image Input | Yes | Supports visual reasoning and image analysis (as of June 2026) | | Image Output | Unconfirmed | Model page only lists text output; native image output not supported (as of June 2026) | | Audio Input/Output | No | Not supported (as of June 2026) | | Video Input/Output | No | Not supported (as of June 2026) |

OpenAI's o3 model page shows support only for text input/output and image input; audio and video are not supported.

What are the limitations of o3?

o3 is not the default choice for all AI workloads. Its reasoning-oriented design results in slower response times compared to lightweight models; OpenAI marks o3's speed as "slowest" in model attributes.

Additionally, o3's context window is 200,000 tokens, output is limited to text, it does not natively support audio or video, and the model page indicates no support for fine-tuning. Its knowledge cutoff is June 1, 2024, so for current events, pricing, regulations, market, or product status questions, retrieval or external verification is needed.

This reflects general AI limitations: unless explicitly stated by OpenAI, o3 may still generate errors, incomplete responses, or overconfident outputs. Legal, medical, financial, security, and compliance scenarios should be reviewed by professionals.

What are the best application scenarios for o3?

| Application Scenario | Why o3 is suitable | Key Limitations | | -------------------------------- | -------------------------------------------------------------- | ---------------------------------------------- | | Complex Code Review | Suitable for multi-step reasoning, covering bugs, architecture, trade-offs | Slower response than small models | | Technical Document Analysis | Handles long prompts and image inputs like charts or flowcharts | 200K tokens large but not unlimited | | Scientific and Math Reasoning | Designed for high-difficulty reasoning tasks | Outputs still require human verification | | Visual Reasoning | Can analyze images and explain findings in text | Does not provide native image outputs | | Structured Planning | Good for breaking down complex workflows | Not suitable for all low-latency chat flows |

How does o3 compare with GPT-4o and Gemini 2.0 Flash?

| Comparison Dimension | o3 | GPT-4o | Gemini 2.0 Flash | Scene Fit | | -------------------------------- | -------------------------------------------------------- | ------------------------------------- | -------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ | | Provider | OpenAI | OpenAI | Google | Choose based on ecosystem preference: OpenAI for o3/GPT-4o workflows, Google for Gemini API or Vertex AI workflows. | | Model Type | Reasoning model | General multimodal GPT model | Fast multimodal model | o3 for deep multi-step reasoning, GPT-4o for broad multimodal assistant tasks, Gemini 2.0 Flash for speed-oriented multimodal applications. | | Context Window | 200,000 tokens | 128,000 tokens | Official Google info states 1M token context window | o3 for long reasoning tasks, GPT-4o for standard multimodal workloads, Gemini 2.0 Flash for ultra-long input contexts. | | Text & Image Input; Text Output | Multimodal input; text output at startup | All three support text & image workflows; o3 better for reasoning, GPT-4o more flexible, Gemini 2.0 Flash faster | | Suitable for deep analysis, flexible multimodal interaction, speed, and long context needs. | | API Pricing | $2 per million input / $8 per million output tokens | $2.50 per million input / $10 per million output tokens | Gemini API priced by tier and SKU | o3 for reasoning quality, GPT-4o for balanced multimodal, Gemini 2.0 Flash for high volume, speed, and Google ecosystem integration. | | Scene Fit | Complex reasoning, code, technical analysis | General multimodal applications and flexible assistant workflows | Speed-oriented and long context multimodal workflows | o3 for deep analysis, GPT-4o for flexible multimodal, Gemini 2.0 Flash for speed and long context. |

GPT-4o, as a general multimodal comparison, lists support for text and image input, text output, 128,000 token context, and pricing at $2.50/$10 per million tokens. Google describes Gemini 2.0 Flash as supporting native tool invocation, multimodal input, text output (initial phase), with a 1M token context window.

How to access o3 via Gate.AI?

Gate.AI offers an OpenAI-compatible API, with base URL and model ID openai/o3. Gate.AI documentation confirms Bearer token authentication, OpenAI-compatible format, pay-as-you-go pricing, POST /chat/completions for chat, GET /models for model listing. They specify the correct API path as /openai/v1, not /v1.

Python example

python from openai import OpenAI import os

client = OpenAI( api_key=os.environ["GATE_AI_API_KEY"], base_url="", )

completion = client.chat.completions.create( model="openai/o3", messages=[ { "role": "system", "content": "You are a helpful AI assistant." }, { "role": "user", "content": "Analyze the trade-offs of using a reasoning model for code review." } ], )

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

curl example

bash curl /chat/completions
-H "Authorization: Bearer $GATE_AI_API_KEY"
-H "Content-Type: application/json"
-d '{ "model": "openai/o3", "messages": [ { "role": "system", "content": "You are a helpful AI assistant." }, { "role": "user", "content": "Analyze the trade-offs of using a reasoning model for code review." } ] }'

Developers can also list available models before deployment:

bash curl /models
-H "Authorization: Bearer $GATE_AI_API_KEY"

Through Gate.AI, developers can use a unified OpenAI-compatible request mode to access supported models, explicitly selecting models via the model field. This document does not merge OpenAI's official pricing with Gate.AI billing unless Gate.AI explicitly announces the pricing for that path.

Frequently Asked Questions

What is the context window size of o3?

OpenAI lists o3's context window as 200,000 tokens, with a maximum output length of 100,000 tokens (as of June 2026).

What is the price of o3?

OpenAI's published pricing for o3 is $2.00 per million input tokens, $0.50 per million cached input tokens, and $8.00 per million output tokens (as of June 2026).

How can developers access o3 via Gate.AI?

Use Gate.AI's OpenAI-compatible base URL, authenticate with GATE_AI_API_KEY, and send chat-completions requests with model ID set to openai/o3.

Is o3 better than GPT-4o or Gemini 2.0 Flash?

Not necessarily. o3 is suitable for complex reasoning tasks, GPT-4o for general multimodal workflows, and Gemini 2.0 Flash for speed-oriented, long-context multimodal tasks.