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OpenAI Inc.

o1:high

The o1 series of models are trained with reinforcement learning to perform complex reasoning. o1 models think before they answer, producing a long internal chain of thought before responding to the user. The o1 reasoning model is designed to solve hard problems across domains. The knowledge cutoff for o1 and o1-mini models is October, 2023.

👁Vision🧠Reasoning🔧Tool calling⚡Caching
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Specifications

Context window200K tokens
Max output100K tokens
API typechat
AddedDec 17, 2024
Model IDopenai/o1:high
Data retentionYes (30 days)
Used for trainingNo
Provider location🇺🇸 US
Privacy policyOpenAI Privacy Policy →

Benchmarks

Released 2024-12
SWE-Bench Verifiedcoding
48.9%

Resolving real GitHub issues from 12 popular Python repositories.

GPQA Diamondreasoning
78.0%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

MMLU Proknowledge
83.5%

Massive Multitask Language Understanding across 57 academic subjects.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality — always test on your own workload.

Pricing

Input / 1M
$15.00
Output / 1M
$60.00
Cache write / 1M
$15.00
Cache read / 1M
$7.50
Estimated cost
100K input + 10K output$2.10
1M input + 100K output$21.00
10M input + 1M output$210.00

Requesty charges exactly what the upstream provider charges — no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to openai/o1:high.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="openai/o1:high",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

Other OpenAI Inc. models

gpt-5.5
1.1M ctx$5.00/1M
gpt-5.5-pro
1.1M ctx$30.00/1M
gpt-5.4-nano
400K ctx$0.20/1M
gpt-5.3-chat
128K ctx$1.75/1M
gpt-5.4-mini
400K ctx$0.75/1M
gpt-5.4-pro
1.1M ctx$30.00/1M

Frequently asked questions

How much does o1:high cost?
o1:high is priced at $15.00 per million input tokens and $60.00 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges — we don't add markup.
What is the context window of o1:high?
o1:high has a context window of 200K tokens, with a maximum output of 100K tokens per response. That's roughly 267 words of input you can fit in a single prompt.
How does o1:high perform on benchmarks?
o1:high scores 94.8% on MATH, 92.4% on HumanEval, 83.5% on MMLU Pro. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can o1:high do?
o1:high supports vision input, tool calling, extended reasoning, prompt caching. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use o1:high with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "openai/o1:high". The Quickstart above shows Python, JavaScript and cURL snippets.

Access o1:high through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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