o4 Mini Deep Research

o4 Mini Deep Research by OpenAI excels in the Coding category, where it ranks #32 with a composite score of 81/100. o4-mini-deep-research is OpenAI's faster, more affordable deep research model—ideal for tackling complex, multi-step research tasks. Note: This model always uses the 'web_search' tool which adds additional cost. It is particularly strong in areas highlighted by its top benchmark performance and adoption metrics, making it suitable for both individual developers and enterprise teams looking for a reliable coding solution.

o4 Mini Deep Research is priced at $2.00 per million input tokens and $8.00 per million output tokens (USD). Contact the provider for volume discounts and enterprise pricing. Pricing is competitive within the coding category and reflects the model's quality-to-cost ratio.

In the Coding category, o4 Mini Deep Research holds rank #32 out of 341 models tracked. Its quality rank is #32 and adoption rank is #32. You can use our comparison tool at /compare to see detailed side-by-side metrics with specific alternatives. Key differentiators include its composite scoring across benchmarks, community sentiment, and real-world adoption rates.

o4 Mini Deep Research has been evaluated across 6 different signals. Its strongest areas include Capabilities (100/100), Benchmarks (85/100), Pricing (92/100). These scores are derived from industry-standard benchmarks, community ratings, and real-world performance metrics. The composite score of 81/100 reflects a weighted combination of all tracked signals.

o4 Mini Deep Research is a paid model, though some providers may offer trial credits or limited free tiers for evaluation. Check OpenAI's website for current free tier availability and promotional offers.

o4 Mini Deep Research supports a 200K token context window (200,000 tokens total). That translates to roughly 150,000 words in a single prompt. This is large enough to process entire codebases, research papers, or long conversation histories in one shot.

o4 Mini Deep Research can generate up to 100K output tokens (100,000 tokens) per response. That is roughly 75,000 words. This is enough for generating complete code files, detailed reports, or long-form content in a single response.

o4 Mini Deep Research supports image understanding (vision), function/tool calling, structured JSON output, extended reasoning/chain-of-thought, web search, streaming responses. Function calling lets you integrate it with external APIs and tools programmatically. Vision support means it can analyze images, screenshots, and diagrams alongside text. These capabilities determine which workflows and integrations the model can handle natively.

o4 Mini Deep Research was developed by OpenAI. It was released on October 10, 2025. You can access it through OpenAI's API. Check our provider page for all models from OpenAI and how they compare against each other.

Pick o4 Mini Deep Research when you need top-tier performance and can justify the cost for quality-critical tasks like production code generation, complex reasoning, or enterprise deployments. If your task is straightforward text completion or classification, a cheaper model might give you 90% of the quality at a fraction of the price. Run a quick benchmark on your actual use case before committing.

You can access o4 Mini Deep Research through OpenAI's API using standard HTTP requests or their official SDK. Most providers support OpenAI-compatible endpoints, so switching between models often requires changing just the model name in your API call. Streaming is supported for real-time token-by-token output. For production use, implement proper error handling, rate limiting, and cost monitoring.