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o4-mini

Microsoft Azure AI/@swedencentral/chat

o4-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.More
Compare 3 providersAll models →

Which id to call

azure/o4-mini@swedencentral

This exact deployment on Microsoft Azure AI in swedencentral, with no routing and no failover. Send it as the model field.

Input /1M

$1.21

$0.30 cached

Output /1M

$4.84

4.0x input

Context

200K

100K output

Added

Apr 2025

chat

Capabilities 4/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What o4-mini costs

Provider prices per 1M tokens, updated September 5, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

$1.21

Output /1M

$4.84

Cache write /1M

-

Cache read /1M

$0.30

What a workload costs

100K input + 10K output
$0.17
1M input + 100K output
$1.69
10M input + 1M output
$16.94

At the rates above, before caching. A cache read costs $0.30 per 1M, so repeated context lands under these figures.

model=

Which id to call

One base url, https://router.requesty.ai/v1, and one key for every id here.

azure/o4-mini@swedencentral

This exact deployment on Microsoft Azure AI in swedencentral, with no routing and no failover. Send it as the model field.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.

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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="azure/o4-mini@swedencentral",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window200K tokens
Max output100K tokens
API typechat
AddedApr 2025
Model id
Data retentionNone
Used for trainingNo
Served from🇪🇺 EU
Privacy policyMicrosoft Privacy Statement →

Released 2025-04-16

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

GPQA Diamondreasoning
78.4%

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

Intelligence Indexreasoning
26.1%

Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.

Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.

Same provider

More from Microsoft Azure AI

Newest first, on the same provider and the same key.

gpt-6-astra

1.1M ctx/$10.00/1M/eastus2

gpt-5.6-luna

1.1M ctx/$0.20/1M/eastus2

openai-responses/gpt-5.6-luna

1.1M ctx/$0.20/1M/eastus2

gpt-5.6-luna

1.1M ctx/$0.22/1M/swedencentral

openai-responses/gpt-5.6-luna

1.1M ctx/$0.22/1M/swedencentral

gpt-5.6-terra

1.1M ctx/$2.00/1M/eastus2

Reference

o4-mini questions

How much does o4-mini cost?

o4-mini is priced at $1.21 per million input tokens and $4.84 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. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of o4-mini?

o4-mini 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 o4-mini perform on benchmarks?

o4-mini scores 90.7% on Math Index, 90.7% on AIME 2025, 85.9% on LiveCodeBench. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.

What can o4-mini do?

o4-mini supports tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use o4-mini 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 "azure/o4-mini@swedencentral". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run o4-mini through Requesty?

Yes. o4-mini runs through Requesty's OpenAI-compatible API, served from Microsoft Azure AI in swedencentral. You do not host the model yourself: point base_url at Requesty, set the model to "azure/o4-mini@swedencentral", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

What region is this deployment?

This variant of o4-mini is deployed in swedencentral. Region-specific endpoints matter for data residency, latency to your users, and compliance requirements (GDPR, HIPAA). Other regions for the same model may be listed on the Microsoft Azure AI provider page.

Call o4-mini through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.

All Microsoft Azure AI models