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Blended $/1M across tracked versions of this line.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-04-28 · Source: legacy_model_catalog
Complex reasoning, analysis, planning and multi-step problem solving where answer quality matters more than raw cost.
The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...
o1-pro is a Reasoning model from OpenAI (US). HotON.ai tracks it at $150.00 per 1M input tokens and $600.00 per 1M output tokens, with a 200K-token context window. Its composite efficiency score is 76/100 at an estimated $0.600 per successful task.
o1-pro is tracked at $150.00 per 1M input tokens and $600.00 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $487.50 per 1M tokens. Figures are illustrative demo data.
Complex reasoning, analysis, planning and multi-step problem solving where answer quality matters more than raw cost.
o1-pro supports up to a 200K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, o1-pro is cheaper than 0% of models on input price and ranks #523 of 537 by overall efficiency.
Yes — grok-4-fast-reasoning is a lower-cost option at $0.50 per 1M output tokens, while still covering similar Reasoning use cases. Compare them side by side on HotON.ai.
Ready to paste into articles, papers or AI prompts — prices and date refresh with the live data.
HotON.ai — o1-pro (OpenAI): $150.00/1M input, $600.00/1M output, as of 2026-04-28. https://hoton.ai/en/models/openai-o1-proPricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.