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o3:flex

O3 Flex is a cheaper version of the o3 model

👁Vision🧠Reasoning🔧Tool calling⚡Caching
Try o3:flexCompareDocs

Specifications

Context window200K tokens
Max output100K tokens
API typechat
AddedApr 16, 2025
Model IDopenai/o3:flex
Data retentionYes (30 days)
Used for trainingNo
Provider location🇺🇸 US
Privacy policyOpenAI Privacy Policy →

Benchmarks

Released 2025-04
SWE-Bench Verifiedcoding
71.7%

Resolving real GitHub issues from 12 popular Python repositories.

GPQA Diamondreasoning
83.3%

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

MMLU Proknowledge
86.9%

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
$1.00
Output / 1M
$4.00
Cache write / 1M
$1.00
Cache read / 1M
$0.25
Estimated cost
100K input + 10K output$0.14
1M input + 100K output$1.40
10M input + 1M output$14.00

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/o3:flex.

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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/o3:flex",
    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 o3:flex cost?
o3:flex is priced at $1.00 per million input tokens and $4.00 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 o3:flex?
o3:flex 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 o3:flex perform on benchmarks?
o3:flex scores 95.3% on MATH, 95.1% on HumanEval, 91.6% on AIME 2024. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can o3:flex do?
o3:flex 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 o3:flex 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/o3:flex". The Quickstart above shows Python, JavaScript and cURL snippets.

Access o3:flex 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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