AI 모델 인텔리전스

OpenAI: o1

helicone/o1

제공: helicone · 패밀리: o · 출시 2025-01-01 · 지식 컷오프: 2025-01

$15.00
입력 / 1M 토큰
$60.00
출력 / 1M 토큰
200K
컨텍스트 창
100K
최대 출력

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

기능

도구 호출추론? 구조화 출력첨부오픈 웨이트온도 제어
모달리티: 입력 text · 출력 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding7
  • Tool calling0/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)6/20
  • Provider availability1/10
Agents16
  • Tool calling0/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output0
  • Structured output / JSON mode0/50
  • Tool calling0/20
  • Temperature control0/10
  • Price-friendly for high-volume0/20
Cost efficiency21
  • Headline price (log-scaled)16/95
  • Has prompt-cache pricing5/5
Long context55
  • Context window (100K → 2M)45/90
  • Has published price for full window10/10
Production-readiness65
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$105
$0.10 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$210
$0.02 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$60.00
$0.06 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$180
$0.18 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$216
$0.22 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

가격 상세

추천 가격 제공자: helicone · o1

$15.00
입력
$60.00
출력
$7.50
캐시 읽기

1곳 제공사에서 이용 가능

제공자제공자 모델 ID입력 / 1M출력 / 1M컨텍스트출시일
Helicone
helicone
o1$15.00$60.00200K2025-01-01

Frequently asked questions

How much does OpenAI: o1 cost?

OpenAI: o1 costs $15.00 per 1M input tokens and $60.00 per 1M output tokens, sourced from helicone. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of OpenAI: o1?

OpenAI: o1 has a context window of 200K tokens, with a max output of 100K tokens per reply. This is the total combined size of prompt + completion.

Does OpenAI: o1 support tool calling?

No. OpenAI: o1 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does OpenAI: o1 support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for OpenAI: o1 in our data source. Verify with helicone's official documentation before relying on it in production.

Can OpenAI: o1 accept image input?

No. OpenAI: o1 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is OpenAI: o1 open-weight?

No. OpenAI: o1 is a proprietary model — only helicone (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to OpenAI: o1?

If OpenAI: o1 doesn't fit, consider OpenAI o3 Pro, OpenAI o4 Mini, OpenAI o3 Mini. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

More helicone models

Capability lists this model is in

마지막 업데이트:

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.