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o4-mini:flex

o3-mini is OpenAI's most recent small reasoning model, providing high intelligence at the same cost and latency targets of o1-mini. o3-mini also supports key developer features, like Structured Outputs, function calling, Batch API, and more. Like other models in the o-series, it is designed to excel at science, math, and coding tasks.

🧠Reasoning🔧Tool calling⚡Caching
Try o4-mini:flexCompareDocs

Specifications

Context window200K tokens
Max output100K tokens
API typechat
AddedApr 16, 2025
Model IDopenai/o4-mini:flex
Data retentionYes (30 days)
Used for trainingNo
Provider location🇺🇸 US
Privacy policyOpenAI Privacy Policy →

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model — check the base model page or the OpenAI Inc. models overview.

Pricing

Input / 1M
$0.55
Output / 1M
$2.20
Cache write / 1M
$0.55
Cache read / 1M
$0.14
Estimated cost
100K input + 10K output$0.0770
1M input + 100K output$0.77
10M input + 1M output$7.70

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/o4-mini: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/o4-mini: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-mini
400K ctx$0.75/1M
gpt-5.3-chat
128K ctx$1.75/1M
gpt-5.4-nano
400K ctx$0.20/1M
gpt-5.4-pro
1.1M ctx$30.00/1M

Frequently asked questions

How much does o4-mini:flex cost?
o4-mini:flex is priced at $0.55 per million input tokens and $2.20 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 o4-mini:flex?
o4-mini: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.
What can o4-mini:flex do?
o4-mini:flex supports 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 o4-mini: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/o4-mini:flex". The Quickstart above shows Python, JavaScript and cURL snippets.

Access o4-mini: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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