OpenAIactive

o4 Mini Deep Research

Released at: October 10, 2025

API StatusAvailable for integration
Context Window200,000 tokens✓ verified today
Input Price / MTok$2.00✓ verified today
Output Price / MTok$8.00✓ verified today

Model Overview

OpenAI · Active Model

  • Long-Context
  • API Available
  • Vetted Benchmarks
  • Production Ready

o4 Mini Deep Research by OpenAI — Technical Architecture, Empirical Benchmarks & API Specs§

1. Executive Summary & Core Positioning§

o4 Mini Deep Research is an advanced artificial intelligence model engineered by OpenAI. Tailored for complex multi-step reasoning, programming synthesis, and extended document comprehension, o4 Mini Deep Research represents a key architectural iteration in the OpenAI model family. First released in 2025-10-10, it serves enterprise developers, research teams, and autonomous system architects requiring strict instruction compliance.

Featuring an input capacity of 200,000 tokens (approximately 267 words), o4 Mini Deep Research processes multi-file code repositories, lengthy technical reports, and complex prompts in a single inference call.


2. Technical Architecture & Verified Specifications§

Official specification breakdown for o4 Mini Deep Research based on verified provider metadata:

  • Model Name: o4 Mini Deep Research
  • Developer / Provider: OpenAI
  • Context Window Capacity: 200,000 tokens (~267 words)
  • Modality Support: Text, Code
  • API Availability: Available via API Gateway
  • Tool-Calling Accuracy Score: Pending Empirical Benchmark
  • Time to First Token (TTFT): Varies by Host Provider

3. Benchmark Evaluations & Performance Metrics§

o4 Mini Deep Research undergoes standardized evaluation across key industry benchmark suites:

  • MMLU (Massive Multitask Language Understanding): Evaluates multi-subject knowledge across STEM, humanities, and social sciences.
  • HumanEval & SWE-bench: Assesses functional Python code synthesis and real-world software engineering bug resolution.
  • GSM8K & MATH: Tests multi-step arithmetic reasoning and formal mathematical proof construction.
  • Chatbot Arena ELO: Evaluates human preference, instruction following, and conversational quality against rival models.

4. Developer API & Integration Specs§

Programmatic integration for o4 Mini Deep Research follows standard OpenAI-compatible REST endpoints.

import os
import requests

api_key = os.getenv("MODEL_API_KEY")
url = "https://openrouter.ai/api/v1/chat/completions"

headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

payload = {
    "model": "o4-mini-deep-research",
    "messages": [
        {"role": "system", "content": "You are a senior software architect and AI system evaluator."},
        {"role": "user", "content": "Analyze system architecture bottlenecks and suggest refactoring strategies."}
    ],
    "temperature": 0.1,
    "max_tokens": 2048
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

5. Production Use Cases & Deployment Scenarios§

5.1 Autonomous Agents & Tool Execution§

Given its instruction compliance and tool-calling capabilities (Pending Empirical Benchmark), o4 Mini Deep Research is frequently integrated as the reasoning engine for autonomous software agents, browser automation pipelines, and API orchestrators.

5.2 Enterprise Document Synthesis§

With its 200,000 tokens input capacity, engineering and legal teams process full regulatory filings, annual corporate disclosures, and technical documentation directly without context loss.

5.3 Programmatic Code Generation§

Development teams utilize o4 Mini Deep Research for automated code generation, pull request audits, unit test suite creation, and language migration (e.g. Python to Rust).


6. Token Economics & Pricing Breakdown§

Inference pricing per million tokens for o4 Mini Deep Research:

  • Input Token Cost: $2.00 per MTok
  • Output Token Cost: $8.00 per MTok
  • Prompt Caching Discounts: Supported on selected API providers (up to 50% savings on repeated prompt prefixes)
  • Batch Processing: Available for non-latency-sensitive bulk inference workloads

7. Comparative Specification Matrix§

Metric / Parameter**o4 Mini Deep Research**Provider Ecosystem Baseline
DeveloperOpenAIIndustry Average
Context Window200,000 tokens128,000 tokens
Input Price / MTok$2.00Variable
Output Price / MTok$8.00Variable
API AccessSupportedStandard

8. Frequently Asked Questions (FAQ)§

Q: What is o4 Mini Deep Research's context window limit?§

A: o4 Mini Deep Research supports an input context window of 200,000 tokens.

Q: What is the API pricing for o4 Mini Deep Research?§

A: o4 Mini Deep Research is priced at $2.00 per million input tokens and $8.00 per million output tokens.

Q: Is o4 Mini Deep Research accessible via API?§

A: Yes, o4 Mini Deep Research is available for programmatic integration.

Developer
OpenAI✓ verified today
Release Date
October 10, 2025✓ verified today
Context Window
200,000 tokens267 words✓ verified today
API Access
Publicly AvailableIntegrate via official API✓ verified today
Input Cost
$2.00per million tokens✓ verified today
Output Cost
$8.00per million tokens✓ verified today
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Vetted Benchmarks

MMLU(estimated)Score: 75.4% (Top 81%)
HumanEval(estimated)Score: 71.6% (Top 82%)
MATH(estimated)Score: 41.4% (Top 97%)
MT-Bench(estimated)Score: 7.9 (Top 98%)
GPQA(estimated)Score: 28.8% (Top 97%)
HellaSwag(estimated)Score: 76.0% (Top 96%)

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Originally published on llmdb.app

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