The original chain-of-thought GPT—still strong in math.
Price per 1 million tokens
per 1M tokens you send
per 1M tokens you receive
Input tokens represent the text you send to the model for processing. Output tokens represent the model's generated response. Pricing is set by OpenAI and reflects current API rates as of October 2025.
per month
per month
per month
ChatGPT o1 by OpenAI is a reasoning‑focused AI model built for analysis, planning, and high‑accuracy answers.
OpenAI
Text
Text-only processing
200000 tokens
Maximum tokens per request
$15.00
per 1M input tokens
$60.00
per 1M output tokens
ChatGPT o1 is a large language model from OpenAI designed for real‑world applications where speed, quality and cost all matter. It’s priced at $15.00 per million input tokens and $60.00 per million output tokens, so teams can estimate usage‑based spend with simple math.
The model supports a context window of about 200,000 tokens, which is enough for long chats, multi‑document prompts, or passing rich system instructions without constant truncation. Compared with purely fast chat models, it devotes more compute to structured, step‑wise reasoning. That makes it a strong choice for planning, data analysis write‑ups, multi‑step transformations, and agent loops where correctness beats raw speed.
In stack choices, many teams compare ChatGPT o1 against Claude 4 Opus. The trade‑off usually comes down to latency tolerance, budget per request, and whether you need image understanding or deeper chain‑of‑thought style reasoning. If you’re cost‑sensitive, keep prompts concise, cache system instructions, and stream outputs so users perceive faster response. If quality is the priority, add brief exemplars and explicit success criteria in the prompt; small guidance often yields outsized gains.
For production, pair the model with guardrails (content filters, schema validators) and log prompts/responses for offline evaluation. Finally, create simple comparison tests—five to ten representative tasks from your app—to verify this model’s answers, latency and cost against your alternatives before you commit. To control spend, consider tiering workloads: route routine queries to a cheaper sibling and reserve this model for complex or customer‑visible moments. Add retries with temperature control, and prefer JSON‑mode or tool calling for structured outputs that slot directly into your pipeline without brittle parsing.
ChatGPT o1 is a AI model from OpenAI. It emphasizes step‑wise reasoning for harder problems and planning tasks. Pricing is $15.00 per 1M input tokens and $60.00 per 1M output tokens. The context window is roughly 200,000 tokens, allowing long prompts and documents. Common uses include chat assistants, summarization, knowledge search, report drafting, and, when supported, image understanding or tool use. It integrates well into web apps, backends, and automation pipelines where latency and reliability matter.
Tiny but surprisingly clever GPT that you can run on a phone-class chip.
Budget GPT-4o—picks up images, speaks text, costs peanuts.
Mid-sized GPT-4.1—the sweet spot for most apps.
Join only me, who has switched to API.chat and is saving on AI expenses while enjoying a better experience.