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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 latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...
o1 is a Reasoning model from OpenAI (US). HotON.ai tracks it at $15.00 per 1M input tokens and $60.00 per 1M output tokens, with a 200K-token context window. Its composite efficiency score is 76/100 at an estimated $0.060 per successful task.
o1 is tracked at $15.00 per 1M input tokens and $60.00 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $48.75 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 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 is cheaper than 2% of models on input price and ranks #524 of 535 by overall efficiency.
Yes — grok-4-1-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 (OpenAI): $15.00/1M input, $60.00/1M output, as of 2026-04-28. https://hoton.ai/en/models/openai-o1Pricing 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.