Capabilities
7-day heat trend
−8.8%Pricing breakdown
Typical 3:1 output-to-input mix, per 1M tokens
Estimated monthly cost by workload
Market position
- Cheaper than 7% of tracked models
- Faster than 66% of tracked models
- Efficiency rank: #1031 of 1105
Best suited for
Complex reasoning, analysis, planning and multi-step problem solving where answer quality matters more than raw cost.
About o4-mini-deep-research
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.
o4-mini-deep-research is a Reasoning model from OpenAI (US). HotON.ai tracks it at $2.00 per 1M input tokens and $8.00 per 1M output tokens, with a 200K-token context window, ~156 tokens/sec throughput and 100.0% availability. Its composite efficiency score is 86/100 at an estimated $0.008 per successful task.
Compare o4-mini-deep-research
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Frequently asked questions
How much does o4-mini-deep-research cost per 1M tokens?+
o4-mini-deep-research is tracked at $2.00 per 1M input tokens and $8.00 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $6.50 per 1M tokens. Figures are illustrative demo data.
What is o4-mini-deep-research best for?+
Complex reasoning, analysis, planning and multi-step problem solving where answer quality matters more than raw cost.
How fast is o4-mini-deep-research?+
o4-mini-deep-research delivers about 156 tokens/sec with 100.0% tracked availability, suitable for latency-sensitive, real-time applications.
Is o4-mini-deep-research cheaper than other AI models?+
Within the HotON.ai tracked set, o4-mini-deep-research is cheaper than 7% of models on input price and ranks #1031 of 1105 by overall efficiency.
Related models
Pricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Speed, availability and efficiency are modeled estimates.