o3 Pro

OpenAI chatreasoningtool_usevision Long

API ID: openai/o3-pro-2025-06-10

Input Price
$20.00
/1M tokens
Output Price
$80.00
/1M tokens

About o3 Pro

The o-series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o3-pro model uses more compute to think harder and provide consistently better answers. Note that BYOK is required for this model. Set up here: https://openrouter.ai/settings/integrations

๐Ÿ’ฐ
Price Ranking
#1231 lowest price among 1240 Chat models

Model Specifications

Context Length
200k
Max Output
100k
Release Date
2025-06-10
Capabilities
chat reasoning tool_use vision
Input Modalities
textfileimage
Output Modalities
text

Best For

  • Complex reasoning, math problems, multi-step logic
  • Image analysis, document understanding, visual Q&A
  • Conversations, content writing, general assistance

Consider Alternatives For

  • Simple Q&A (cheaper models available)

๐Ÿ’ฐ Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$33.00
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$1020.00
/month
1000 tickets/day, ~800 tokens each
Data Analysis Pipeline
$1410.00
/month
500 analyses/day, ~2k tokens each

OpenAI Model Lineup

Compare all models from OpenAI to find the best fit

Model Input Output Context Capabilities
o3 Pro Current Free Free 200k chat reasoning tool_use vision
GPT-3.5 Turbo 16k (older v1106) Free Free 16k chat
GPT-3.5 Turbo 16k (older v1106) Free Free 16k chat
GPT-4 32k Free Free 33k chat
GPT-4 32k Free Free 33k chat
GPT-4 32k (older v0314) Free Free 33k chat

Similar Models from Other Providers

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Output: $75.00
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Input: $15.00
Output: $75.00
Context: 200k
Anthropic Claude Opus 4
Input: $15.00
Output: $75.00
Context: 200k
Anthropic Claude Opus 4
Input: $15.00
Output: $75.00
Context: 200k

๐Ÿš€ Quick Start

Get started with o3 Pro API

OpenAI Python SDK
from openai import OpenAI
client = OpenAI()

response = client.chat.completions.create(
    model="openai/o3-pro-2025-06-10",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)