o3 Deep Research

OpenAI chatvisionreasoningtool_use Long

API ID: openai/o3-deep-research-2025-06-26

Input Price
$10.00
/1M tokens
Output Price
$40.00
/1M tokens

About o3 Deep Research

o3-deep-research is OpenAI's advanced model for deep research, designed to tackle complex, multi-step research tasks. Note: This model always uses the 'web_search' tool which adds additional cost.

๐Ÿ’ฐ
Price Ranking
#1215 lowest price among 1240 Chat models

Model Specifications

Context Length
200k
Max Output
100k
Release Date
2025-10-10
Capabilities
chat vision reasoning tool_use
Input Modalities
imagetextfile
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
$16.50
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$510.00
/month
1000 tickets/day, ~800 tokens each
Data Analysis Pipeline
$705.00
/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 Deep Research Current Free Free 200k chat vision reasoning tool_use
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

Cross-brand alternatives with similar capabilities

Anthropic Claude Opus 4.1 (batch)
Input: $7.50
Output: $37.50
Context: 200k
Anthropic Claude Opus 5 (Fast)
Input: $10.00
Output: $50.00
Context: 1.0M
Anthropic Claude Fable Latest
Input: $10.00
Output: $50.00
Context: 1.0M
Anthropic Claude Fable 5
Input: $10.00
Output: $50.00
Context: 1.0M

๐Ÿš€ Quick Start

Get started with o3 Deep Research API

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

response = client.chat.completions.create(
    model="openai/o3-deep-research-2025-06-26",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)