o4 Mini Deep Research
VerifiedMultimodal research model with massive context for complex analysis.
About o4 Mini Deep Research
Designed as a closed-source multimodal system, o4 Mini Deep Research handles inputs across files, images, and text. Its 200000-token context window enables processing of large documents and visual data together. The architecture focuses on sustained reasoning over extended inputs without public parameter details.
Strengths center on integrating diverse modalities for thorough examination of research materials. It maintains coherence across lengthy contexts while analyzing combined text and visual content. Users benefit from its ability to manage complex queries involving multiple data types in one session.
Typical usage includes academic research, market analysis, and technical document review where images and files must be examined alongside text. Professionals leverage it for compiling insights from extensive multimodal datasets. The model suits scenarios requiring persistent context across large-scale inputs.
Capabilities
How o4 Mini Deep Research compares
o4 Mini Deep Research (striped bar) vs other multimodal on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · o4 Mini Deep Research ranks #79 of 124
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
In-depth academic literature synthesis
The 200k context window allows processing entire research paper collections and datasets in one pass for comprehensive thematic analysis and gap identification.
Multimodal report generation from mixed sources
It combines text, charts, and images from lengthy documents to produce structured summaries and insights for business or scientific reporting.
Extended multi-step investigative workflows
Supports chaining complex queries across large knowledge bases while maintaining coherence for tasks like policy analysis or technical due diligence.
Strengths & limitations
Strengths
- +Strong handling of large contexts for detailed research
- +Effective integration of text, image, and file inputs
- +Specialized for in-depth information gathering and synthesis
- +Flexible multimodal input support
Limitations
- –Mini model may trade depth for speed in complex tasks
- –No support for audio or video modalities
- –Research outputs can still require user verification for accuracy
Cost calculator
Estimate what o4 Mini Deep Research would cost for your usage.
Based on o4 Mini Deep Research's $2.00/1M input · $8.00/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "openai/o4-mini-deep-research",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: openai/o4-mini-deep-research
Editor's verdict
o4 Mini Deep Research is OpenAI's proprietary multimodal with a 200K-token context window.
At $8.00 per 1M output tokens, it is premium-priced for its class.
It is available through OpenAI's API and aggregators like OpenRouter.
Best suited to strong handling of large contexts for detailed research and effective integration of text, image, and file inputs.
Frequently asked questions
The model supports a context length of 200000 tokens.
User reviews
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